NISTIR 7553

SlapSegII – Slap Fingerprint 

Segmentation Evaluation II

Testing Procedure and Results

Craig Watson

Patricia Flanagan

Brian Cochran

 
NISTIR 7553

SlapSegII - Slap Fingerprint 

Segmentation Evaluation II

Testing Procedure and Results

Craig Watson 

Patricia Flanagan 

Brian Cochran

Information Technology Laboratory 

Information Access Division 

January 2009

U.S. Department of Commerce 

National Institute of Standards and Technology 

Patrick D. Gallagher, Deputy Director 

 
Acknowledgements 

The authors would like to thank the Federal Bureau of Investigation, Department 

of State and Department of Homeland Security for sponsoring this work. The 

authors would like to thank individuals and organizations identified in the report 

for their input/comments on the testing plan in preparation for this work. The 

authors would also like to thank all those involved with hand marking the ground 

truth data. It was a tedious and time consuming task. 

*Disclaimer 

Specific hardware and software products identified in this report were used in 

order to perform the evaluations described in this document. In no case does 

identification of any commercial product, trade name, or vendor, imply 

recommendation or endorsement by the National Institute of Standards and 

Technology, nor does it imply that the products and equipment identified are 

necessarily the best available for the purpose. 
Contents 

Summary ............................................................................................................................. 1

Caveats ................................................................................................................................ 2

1. Introduction/Background ............................................................................................. 3

2. Purpose of Slap Fingerprint Segmentation (SlapSeg) ................................................. 4

3. SlapSeg 2004 ............................................................................................................... 8

4. SlapSegII ..................................................................................................................... 9

5. Evaluation Data ......................................................................................................... 19

5.1. Dataset Ground Truth ......................................................................................... 19

6. SlapSegII Successful Segmentation Metric ............................................................... 20

6.1. 3-inch Data ......................................................................................................... 20

6.2. 2-inch Data ......................................................................................................... 23

7. Results ....................................................................................................................... 29

8. Future Work ............................................................................................................... 35

Appendix A - Result tables for 3-inch slap images. 

Appendix B - Result tables for 2-inch slap images. 

Appendix C - Detailed segmentation statistics. 

Appendix D - Plots of 3-inch segmentation box centers. 

Appendix E - Plots of 3-inch segmentation box widths and heights. 

Appendix F - Plots of 2-inch segmentation box centers. 

Appendix G - Plots of 2-inch segmentation box widths and heights. 

Appendix H - Confidence intervals for 3-inch segmentation results. 

Appendix I - Confidence intervals for 2-inch segmentation results. 
Summary 

The SlapSegII evaluation is sponsored by the Federal Bureau of Investigation 

and Department of State. The evaluation is being performed to assess the 

current state-of-the-art in slap fingerprint segmentation. The evaluation uses 

operational data from both 2-inch and 3-inch platen live-scan devices. The 3-inch 

platen slap fingerprints are of particular interest because of their use in 

government systems transitioning from 2 finger identification to 10-print 

identification flats. 

The most significant differences between SlapSegII and SlapSeg04 are the 

metrics used to determine successful segmentation and the availability of 3-inch 

slap fingerprint data. SlapSeg04 used fingerprint matching to determine if a 

segmentation algorithm was successful. SlapSegII uses hand marked 

segmentation boxes as a baseline for measuring a successful segmentation. 

The results from SlapSegII are very encouraging. Many of the segmentation 

algorithms tested were able to successfully segment at least 3 fingers from a 2-

inch or 3-inch four finger slap image for 96-99% of the slap images (both right 

and left hand). The 3-inch results combining both right and left hands showed 

that most algorithms were able to segment any 6 finger for more than 99% of the 

slap images. For 2inch by person, most algorithms were successful for 95-99% 

of the slap images. 

The 3-inch thumb slaps proved more difficult to segment than the four finger slap 

images. This type of image is fairly new and presents a couple new issues not 

present in live-scan four finger slaps. First, there is no predictable 

anthropometric finger behavior to assist in segmentation as users generally place 

both fingers at the same vertical position on the platen. In four finger slaps the 

positioning of the four fingers can be used to improve segmentation. Second, 

some users tend to rotate the bottom of their thumbs outward when placing them 

on the platen and the general assumption has been that the 3-inch slap 

fingerprints are not rotated. 

Not surprisingly, the inter-digital crease proved the most difficult edge to correctly 

detect. Even the better performing algorithms saw overall improvement if 

tolerances were relaxed or ignored around the crease. 

Appendix A (3-inch) and Appendix B (2-inch) contain all the tables showing 

successful segmentation rates for individual finger positions, right and left hands, 

and various combinations of finger positions that would be of interest to 

operational systems. Appendix C shows segmentation statistics for each 

algorithm in the evaluation. Appendix D - Appendix G are plots of the 

segmentation box centers and sizes. Appendix H and Appendix I are plots (w/ 

confidence intervals) for the results from Appendix A and Appendix B. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Caveats 

As with any biometrics evaluation, all factors of the testing procedure/evaluation 

should be considered when making policy, planning or operational decisions. 

- The data used in this evaluation is both 2-inch and 3-inch slap image data 

captured on live-scan fingerprint readers. The data is considered operational. 

Data in other operational systems may not have the exact same characteristics 

depending on capture environment, user demographics, sensor type and 

capture policy. 

- The success metric in SlapSegII uses strict limits on how much of the 

fingerprint ridge structure can be cropped during segmentation. This varies 

from previous work in SlapSeg04 which used fingerprint matching when 

determining successful segmentation. 

- What affect will segmentation have on the matching performance of an AFIS 

system? The affect is AFIS dependant. Does the AFIS use pattern-class 

filtering? Over-cropping during segmentation could have a serious negative 

impact on pattern classification. Does the AFIS use all ten fingers for 

matching? The segmentation may not need to correctly segment all the fingers 

to successfully identify a person. 

- What effect does over-cropping have on matcher performance? Some work 

was performed on this issue when determining the segmentation tolerances 

used in this study. More detailed work is already started based on the 

segmentation results from SlapSegII. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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1. Introduction/Background 

In 2004, NIST conducted a fingerprint slap segmentation study [1] to assess the 

state-of-the-art in fingerprint segmentation technology. Given the development of 

new technology it has become necessary to reassess the current state-of-the-art 

of segmentation algorithms. SlapSegII gives providers of this technology the 

opportunity to participate multiple times as their technology improves and 

compare their results to previous results on a fixed standard database. The 

SlapSegII evaluation strategy, data, and measure of successful segmentation are 

discussed in detail in this testing plan. By following the guidelines laid out in this 

document, participants can submit segmentation SDKs for evaluation by NIST as 

part of SlapSegII. 

Fingerprint data is collected and maintained in the form of ten-print cards or 

Identification Flats (ID Flats). Traditional ten-print cards are comprised of the 

rolled impressions of the ten fingers as well as four slap impressions: the left slap 

(four fingers of the left hand), the right slap (the four fingers of the right hand) and 

the left and right thumb slaps. Slaps are taken by pressing the four fingers of 

one hand onto a scanner or fingerprint card simultaneously. The ten-print card 

slaps whether scanned inked cards or live-scan capture are also referred to in 

this document as 2-inch data which refers to the height of the capture area for 

the fingerprint slaps. ID Flats are ten-print fingerprint records which are 

constructed by capturing three discrete impressions: left four finger slap, right 

four finger slap, and both thumbs together. For this document the ID Flats are 

data that was captured on new live-scan devices that use a larger platen that is 3 

inches in height so this data is referred to as 3-inch data. 

Currently the Federal Bureau of Investigation (FBI) receives the majority of their 

fingerprint submissions electronically from live-scan devices, however, tens of 

millions of legacy fingerprint transactions are stored that were originally taken on 

paper cards and electronically converted. The Department of State (DOS) and 

Department of Homeland Security (DHS) US-VISIT program are migrating from 2 

finger capture to 10 print ID Flats capture so the ability to evaluate and improve 

segmentation technology on this type of data will have a significant impact on 

those agencies. 

The most significant differences between SlapSegII and SlapSeg04 are the 

metrics used to determine successful segmentation and the availability of 3-inch 

slap fingerprint data. SlapSeg04 used fingerprint matching to determine if a 

segmentation algorithm was successful. SlapSegII uses hand marked 

segmentation boxes as a baseline for measuring a successful segmentation. By 

conducting the evaluation using the ground truth dataset, NIST can better 

implement success measures to accurately determine the success of the 

segmenter independent of a successful match, thus providing a more accurate 

evaluation of the segmentation process and minimize the amount of human 

verification needed to check segmentation/matcher errors. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Sections 2 and 3 give a general overview of Slap fingerprint segmentation and 

pervious work performed. Section 4-6 are detailed descriptions of the SlapSegII 

evaluation procedures, data, and performance metrics. Section 7 and 8 are the 

major results from SlapSegII and description of future work planned. Appendix A

- Appendix I are detailed result tables and plots from the SlapSegII evaluation. 

2. Purpose of Slap Fingerprint Segmentation (SlapSeg) 

Slap fingerprints are noted for the speed at which they can be collected and 

processed. However, a slap record is an image of multiple fingers. Fingerprint 

images must be matched against individual fingerprint images, not an image of a 

group of fingers. Thus, it is necessary to quickly and accurately separate, or 

segment, the grouped image of prints into individual fingerprint images which can 

be used for matching. 

2.1. Definition 

Slap segmentation is the process by which a single image containing four 

fingerprint images is divided into four images of the individual fingers or by 

finding the fingerprint segmentation positions and using them to separate the 

image into individual images at a later date. The term fingerprint segmentation 

positions refer to the expected positions of each of the four fingers and thumb of 

each hand relative to an adjacent finger of the hand. The fingerprint 

segmentation positions are defined in the ANSI/NIST-ITL 1-2007 data 

transmission standard (type-14 record) [3] for non-rotated segmentation boxes as 

the x-coordinate of the left and right edge and the y-coordinate of the top and 

bottom edge of the segmentation box. For rotated fingerprint images, 

segmentation positions are the x,y coordinates of the four corners of the rotated 

segmentation box. For this evaluation they will be in the following order: top-left 

corner, top-right, bottom-left, and bottom-right. Fingers are conventionally 

numbered as positions 1 and 6 (thumbs on the right and left hands, respectively), 

2 and 7 (index fingers), 3 and 8 (middle fingers), 4 and 9 (ring fingers), and 5 and 

10 (small fingers). Accurately labeling each finger is imperative for future 

matching efforts as well as the ability to correctly detect when fingers are not 

present in the image. 

2.2. Issues 

Slap segmentation can prove difficult due to a variety of scenarios. The most 

common challenge scenarios include fingerprints that are not clearly separated in 

an image, a fingerprint which appears as multiple images in a slap, background 

noise, the “halo” effect, and rotation. Many of these problems are the same as 

those that existed in the SlapSeg04 evaluation but the use of newer 3-inch platen 

capture devices can reduce problems such as finger spacing and rotation. 

Slap segmentation can be adversely affected by fingers that are not clearly 

separated in an image (See Figure 1), which could be due to finger placement at 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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the time of capture. It is also possible that two neighboring fingerprints may have 

been over inked or too wet/oily at the time of capture, in which case a down 

sampling or an improper threshold may result in the fingerprints being detected 

as single component. However, the single component should not be split solely 

due to the large width of the detected component. The preferred method for 

splitting the component depends on the width of the component, the number of 

components detected, and the geometric relationship of the component to the 

other components. 

Figure 1. Middle fingers touching in slap. 

At the opposite end of the spectrum, an excessively dry or under inked finger or a 

fingerprint captured using uneven pressure may be detected as several 

components due to down sampling or improper thresholding. (See Figure 2). 

Whether to merge or delete these components depends on the relationship 

between each sub component and the rest of the components. Segmentation 

algorithms often use contrast equalization to enhance ridge detail and allow for 

better segmentation. Though this process can sometimes improve the matching 

quality of the segmented fingerprint, it sometimes has the opposite effect. 

However, SlapSegII will not judge the effect these changes have on fingerprint 

image quality in regards to matching as SlapSegII is focused on segmentation, 

not matching. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Figure 2. Low Contrast slap image. 

Background noise such as extraneous print lines, printed letters, smudges, etc 

near the boundary of the slap print pose an additional challenge for 

segmentation. (See Figure 3.) “Noise”, which may also be caused by dirt on the 

platen surface of the scanner, is most problematic in low contrast images. 

Figure 3. “Noisy” slap image. 

The “Halo” affect can make segmentation difficult as it introduces noise to the 

image. (See Figure 4.) The “Halo” affect is a moisture build up on platen surface 

of the scanner due to temperature variations (i.e. a warm hand being placed on a 

cool scanning surface). 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Figure 4. Moisture/Condensation on the platen surface. 

Image rotation poses an additional problem when a scanner with a two inch high 

scanning surface is used, as well as in some older paper data which has been 

scanned electronically. (See Figure 5.) 

Figure 5. Slap rotation. 

Amputated fingers could also pose a problem during the segmentation process. 

Livescan capture devices should correctly identify this problem during the 

enrollment process, however older devices may not have captured this 

information and electronically converted fingerprint cards may not have the 

proper flags for amputation. The segmentation software may incorrectly segment 

an image based on missing or amputated fingers. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Figure 6. Slap amputation. 

Often the right and left little finger are not captured or only partially captured 

during the slap enrollment process. Vendors may fail to find these partial little 

fingers or have trouble processing transactions without little fingers. While this is 

actually a livescan capture issue versus a segmentation issue, the resulting 

image can pose challenges to the segmenter. 

Figure 7. Partial little finger. 

3. SlapSeg 2004 

SlapSeg04 [1] was conducted to assess the accuracy of existing slap 

segmentation algorithms in segmenting slap fingerprint images into individual 

fingerprint images, using a variety of operational-quality slap fingerprints. The 

study was conducted by the National Institute of Standards and Technology 

(NIST) on behalf of the Department of Justice (DOJ) Justice Management 

Division (JMD), IDENT/IAFIS Integration Project, with the support of the USA = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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VISIT Program Office of the Department of Homeland Security (DHS) and the 

Federal Bureau of Investigation (FBI). 

The study, which was conducted between October and December of 2004, used 

rolled images to match against the segmented slaps as the measure of 

segmentation success. This required manual checking to verify the results of 

each vendor as a low quality image may have segmented correctly without 

matching to the rolled image. The study examined records from about thirty 

thousand subjects from seven different operational datasets, none of which was 

3-inch fingerprint data. SlapSeg04 incorporated several subtly different 

objectives including measurement of the accuracy of state-of-the-art slap 

segmentation software, assessment of the practicality of segmenting operational 

quality slap fingerprints, determination of the factors that cause slap 

segmentation and matching to fail, and assessment of the ability of segmentation 

algorithms to detect when segmentation was successful. 

4. SlapSegII 

SlapSegII is conducted by NIST in order to provide the ability to assess the 

current state-of-the-art in slap segmentation technology. SlapSegII gives 

vendors the opportunity to participate multiple times as their technology improves 

and compare their results to previous results on the same standard dataset. The 

use of hand marked ground truth segmentation boxes allows NIST to quickly 

analyze and report back results for each segmentation algorithm. 

The study is sponsored by the FBI and DOS. The sponsors require the ability to 

test on large volumes of Sensitive But Unclassified (SBU) data. The FBI is 

accepting submissions consisting only of slap data, while DOS/DHS are currently 

migrating from 2 finger captures to ten finger captures for its US-VISIT program. 

The most efficient method for capturing ten fingers is slap images. Thus the 

sponsors will benefit from knowing what the current state of the art is in slap 

segmentation technology. Vendors will also benefit from the study as they will 

gain the knowledge of how their segmentation implementation will perform on a 

large dataset of operational quality law enforcement data. Thus, the study can 

prove extremely critical for improving segmentation technology. 

4.1. Testing Strategy 

NIST intends to use a measure of successful slap segmentation for SlapSegII 

that requires minimal manual verification of segmented slaps and does not rely 

on the ability to match segmented slap images. This success measure is based 

on comparing segmenter output with “ground truth” segmentation coordinates. In 

order to prove effective, it is imperative to have a controlled test location, 

submission process, and validation data, as well as a clear understanding of the 

input and expected output. 

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4.2. Test Location 

All testing is conducted at the NIST laboratory in Gaithersburg, MD. The lab 

responds to needs for measurement methods, tools, data, and technology. NIST 

researchers collaborate with colleagues in industry, academic institutions, and 

other government agencies. The result is baseline research that advances the 

nation's technology infrastructure and is needed by U.S. industry to continually 

improve technology and services. 

4.3. Who Should Participate 

Makers of commercially available slap fingerprint segmentation software are 

invited to participate in the Slap Fingerprint Segmentation Evaluation II. In 

addition, companies, research organizations, or universities that have developed 

mature prototype or research slap fingerprint segmentation software are invited 

to participate. It is important to note that the segmentation software need not be 

“operational,” nor a production system, nor commercially available. However, the 

software must, at a minimum, be a stable implementation capable of functioning 

as stated in for this document (sections 4.8 - 4.11). Additionally, anonymous 

participation is not permitted. The results of the evaluation are published with 

attribution to the participating organizations. 

4.4. Submission Process 

In order to simplify the submission process, NIST adheres to specific guidelines 

and processes for vendor submissions. NIST has written and maintains the 

control and scoring software. Vendors submit compiled command line 

executables that do not use any graphical user interface (GUI) and run on either 

Red Hat Enterprise Linux 5 or Windows Server 2003 operating systems*. Any 

data generated or obtained during the SlapSegII evaluations, as well as any 

documentation required by the Government from the participants, becomes the 

property of the Government. Participants do not possess a proprietary interest in 

the data and/or submitted documentation. 

4.5. Application Process 

In order to request participation in SlapSegII, potential participants must 

complete and submit the Application to Participate in SlapSegII which is available 

on the SlapSegII website fingerprint.nist.gov/SlapSegII. Incomplete forms are 

not accepted. When completing the application, the Responsible Party must be 

an individual with the authority to commit the organization to the terms in this 

document, and the Point of Contact must be an individual with detailed 

knowledge of the system to be considered for evaluation. 

Participants may withdraw from the SlapSegII evaluations at any time before the 

software to be evaluated is received by NIST, without their participation and 

withdrawal being documented in SlapSegII evaluation results. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Upon receipt of the signed form by NIST, the organization is classified as a 

“Participant”. (NIST must have received the form by the due date as posted on 

the SlapSegII website for inclusion in this initial evaluation report.) Registered 

participants then download the small Validation Dataset from the website. 

4.6. Points of Contact 

The SlapSegII Liaison is the government point of contact for SlapSegII. All 

correspondence should be directed to slapseg@nist.gov, which will be received 

by the SlapSegII Liaison and other SlapSegII personnel. Any correspondences 

may be posted on the FAQ (Frequently Asked Questions) area of the SlapSegII 

website at the discretion of the SlapSegII Liaison. The identity of those persons 

or organizations whose correspondences lead to FAQ postings will not be made 

public in the FAQ. 

4.7. Validation Data 

In order to minimize the variability introduced to testing by the physical 

differences in vendor hardware versus NIST hardware, NIST provides 

sample/validation data to the vendors prior to testing. This validation data is 

used to ensure that the software produces the same results on vendor computers 

and NIST computers. Thus ensuring the software being tested produces the 

required data format during testing. 

4.7.1. Access to SlapSegII Validation Data 

The SlapSegII validation data is supplied to Participants to assist in preparing for 

SlapSegII. The fingerprints in the SlapSegII validation data are representative of 

the SlapSegII test data only in format. Image quality, collection device, and other 

characteristics vary between the Validation and Test Datasets. 

4.7.2. Validation and Submission Process 

Prior to submission of their SDK the participant verifies that their software 

executes on the validation data and produces segmentation information in the 

required format. By utilizing validation data, NIST effectively minimizes the 

potential for errors due to hardware differences prior to testing. 

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After the participant has executed their software on the validation data, the output 

of the validation data is submitted to NIST along with the SDK. Software is sent 

by email (file is encrypted using encryption key provided by NIST, 

procedures are posted on the SlapSegII website) to slapseg@nist.gov, or on 

CD (recommend encrypting the files on the CD) to: 

Slap Fingerprint Segmentation Evaluation II (SlapSegII) Liaison 

National Institute of Standards and Technology 

Information Access Division (894) 

100 Bureau Drive, Stop 8940 

Gaithersburg, MD 20899-8940 

Upon receipt of the SDK and validation output, NIST attempts to reproduce the 

output by executing the SDK on the validation data using a NIST computer. In 

the event of disagreement in the output, if the software is found to be nonfunctional or non-compliant with section 4 of this document, or the validation 

dataset results cannot be replicated by NIST, participants will be notified with a 

detailed description of the problem(s) and given a reasonable opportunity to 

resubmit (as time allows) according to the discretion of the SlapSegII Liaison. 

4.8. Application Inputs 

SlapSegII investigates the accuracy of fingerprint image segmentation systems 

for use with multi-finger slap images. These slap images consist of both 2-inch 

slap data (fingerprint are rotated) and 3-inch slap data (no rotation). The 2-inch 

data contains left and right four finger slap images that are live-scan and 

rescanned ink. The 3-inch data contains left and right four finger slap images and 

both thumbs captured together. All 3-inch data is live-scan. 

The submitted segmentation applications are assumed to run on Windows 

Server 2003 or Red Hat Linux Enterprise 5.0, on x86 platforms*. Other options 

must be approved by the Test Liaison. An application must have a command-line 

interface as specified in this document; no other user interface is permissible. 

The segmentation application must be capable of taking as input an 

uncompressed raw slap image, and outputting the segmentation coordinates as 

specified in section 4.9.1. 

4.8.1. Slap Image Files 

The segmentation application must be capable of processing multi-finger slap 

images stored as raw pixel data files. 

Syntactically correct samples are available on the website 

http://fingerprint.nist.gov/SlapSegII. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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4.8.2. Resolution and Dimensions 

All images for this test are 500 PPI resolution (horizontal and vertical, 

19.7ppmm). The dimension of the 3-inch slap images are 1576 x 1572 pixels 

(80mm x79.9mm, 3.15in x 3.14in). The majority of the 2-inch slap images are 

1600 x 950 pixels (81.3mm x 48.3mm, 3.2in x 1.9in) but can be as large as 1600 

x 1000 pixels (81.3mm x 50.8mm, 3.2in x 2 in). 

4.8.3. Raw File Format 

Raw 8-bit grayscale image files are canonically encoded with black equal to 0, 

white equal to 255, etc.; stored left to right, top to bottom, with one 8-bit byte per 

pixel. The number of bytes in a file is exactly the image width * image height, as 

measured in pixels; there is no header. 

4.8.4. Input Parameters 

The following information is provided as parameters to the segmentation 

application: 

Identifier [-i] 

If this input is given the segmentation algorithm returns the software vendor’s 

point of contact email address without performing any segmentation. This 

function is used to confirm that the correct segmentation algorithm is 

executed. Optionally, the vendor can provide version information after the 

email address.

Type [-t] 

specifies the type of the fingerprint image: 2 (2-inch), 3 (3-inch).

Hand identifier[-h] 

specifies R (right hand ), L (left hand), or T (two thumb, 3-inch only) 

corresponding to the specified slap image. 

Source [-s] 

specifies the source of the fingerprint image: L (livescan), P (paper), or U

(unspecified; could be livescan or paper). 

The parameters (if present) are in the stated order. Parameters are separated by 

spaces or tabs. 

4.9. Application Outputs 

4.9.1. Segmentation Coordinates 

The segmentation output for each input image is multiple lines of text which 

contain the segmentation box coordinates for each expected finger in the slap 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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image. The output coordinate format is based on the type-14 record from 

ANSI/NIST-ITL 1-2007 [3]. 

For 2-inch images the output is the x,y coordinates for all four corners of the 

segmentation box and the angle of rotation (theta) for the fingerprints in the 

image. The corner x,y coordinates are listed in the following order: top-left, topright, bottom-left, and bottom-right. The rotation angle uses positive for clockwise 

rotation and negative for counter-clockwise rotation and is given in degrees of 

rotation. Zero degrees is at vertical. It is anticipated that the vertices form a 

rectangular segmentation box but it is not required in the way they are reported. 

For this evaluation the ground truth boxes are rotated rectangles, it is up to the 

reporting segmentation algorithm whether or not to report rectangular 

segmentation boxes for 2-inch slaps. Figure 8 shows a 2-inch slap image with 

segmentation boxes drawn. 

Figure 8. 2-inch sample showing segmentation boxes, with vertices 

outside image limits.. 

All 3-inch input data is assumed to be vertical/non-rotated and the segmentation 

is the best fit vertical/non-rotated box for each finger in the slap image. The 

segmentation coordinates for the 3-inch slap are the x-position of the left side, xposition of the right side, y-position of the top, and y-position of the bottom of the 

segmentation box. All x,y positions are from the top-left corner (0,0) of the slap 

image.Figure 9 shows a 3-inch slap image with segmentation boxes drawn. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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Figure 9. 3-inch slap image showing segmentation boxes. 

The finger positions are the position codes defined in Table 12 of ANSI/NIST-ITL 

1-2007 [3]: 

01 Right thumb

02 Right index 

03 Right middle

04 Right ring 

05 Right little 

06 Left thumb 

07 Left index 

08 Left middle 

09 Left ring 

10 Left little 

The output is written to a file with the same name as the input file but changing 

the extension from .raw to .sgm. For example if the input file is image.raw the 

output file is image.sgm. The output file is written in the same directory path as 

the input file. Examples for each image type are: 

2-inch Right Hand: 

02,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr

03,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr

04,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr

05,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr 

Theta 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

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2-inch Left Hand: 

07,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr

08,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr

09,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr

10,xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr 

theta 

3-inch Right Hand: 

02,xleft,xright,ytop,ybottom

03,xleft,xright,ytop,ybottom

04,xleft,xright,ytop,ybottom

05,xleft,xright,ytop,ybottom

3-inch Left Hand: 

07,xleft,xright,ytop,ybottom

08,xleft,xright,ytop,ybottom

09,xleft,xright,ytop,ybottom

10,xleft,xright,ytop,ybottom

3-inch Two Thumb: 

01,xleft,xright,ytop,ybottom

06,xleft,xright,ytop,ybottom 

If the segmentation algorithm can’t detect/segment one or more of the fingers it 

must output a -1 after the finger number. For example: 

02,xleft,xright,ytop,ybottom

03,-1 

04,xleft,xright,ytop,ybottom

05,xleft,xright,ytop,ybottom 

4.9.2. Error Codes and Handling 

The segmentation application shall exit with a return code of zero on success. 

The participant must provide documentation of all (non-zero) error or warning 

codes (see section 4.10). 

The application should include error/exception handling so that in the case of a 

crash, the return code is still provided to the calling shell. 

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We request that the following return codes are used: 

Return code Explanation

0 Success 

1 Unable to read input file 

2 Unable to open input file 

10 0 fingers could be segmented 

11 Only 1 finger could be segmented 

12 Only 2 fingers could be segmented, for 4 finger slap image 

13 Only 3 fingers could be segmented, for 4 finger slap image 

20 – 63 Application-specific fatal errors (explained in documentation) 

64 – 127 Application-specific non-fatal warnings (explained in documentation)

All errors, warnings and informational messages are limited to output displayed 

via standard output or standard error. No GUI-type dialog windows are 

permitted. 

4.10. Software and Documentation 

4.10.1. Application type and platform 

The application provided will be command-line driven, and capable of being run 

in non-interactive “batch mode.” No graphical user interface (GUI) is permitted. 

Test participants will provide NIST with binaries only (i.e. no source code) for 

their segmentation application. Testing of segmentation systems is performed on 

commercial, off-the-shelf PCs. Applications running on Red Hat Enterprise Linux 

5 or Microsoft Windows Server 2003 are preferred*; other operating systems 

must be approved by the Test Liaison. 

4.10.2. Installation 

Segmentation software must install and run easily to be evaluated. The 

application shall be immediately executable without use of an installation 

program. Please contact the Test Liaison if an installation program is absolutely 

necessary. The application shall be executable on any number of machines 

without requiring additional machine-specific license control procedures or 

activation. 

It is preferred that the application is packaged as a single executable file. If 

external libraries (such as DLLs) are necessary, they must work from the 

application directory, and not require installation in another location. 

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4.10.3. External Communication 

The segmentation software running on NIST hosts shall not write any data to 

external resources (e.g. server, file, network connections, or other process) other 

than those explicitly allowed in this document. 

4.10.4. Documentation 

Complete documentation of application usage shall be provided, and shall detail 

any additional functionality or behavior beyond what is specified in this 

document. The documentation must define all error and warning codes. 

4.10.5. Speed 

Software that runs excessively slow can’t be evaluated. On average, 

segmentation software should take less than five (5) seconds to segment a slap 

image (using a 2.8 GHZ Pentium Xeon processor). Due to resource limitations, 

software that takes longer than that may not be evaluated. Processing speed is 

noted but will not be a primary evaluation criterion. 

4.11. Validation Data Results 

Participants must test their software using the SlapSegII validation data, and 

email these results to the Test Liaison for validation before sending software to 

NIST for evaluation 

4.12. SlapSegII Calendar (Initial Evaluation) 

Date 

5/8/2008 Announcement/Request for Comments 

5/23/2008 End Comment Period 

6/3/2008 

Release Final Test Plan 

Start Accepting Applications 

6/12/2008 Validation Data Available 

6/27/2008 Last Day for Applications 

8/7/2008 Validation Data Results Submission 

Deadline 

8/13/2008 Software Submission Deadline 

January 2009 Results Report Issued 

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5. Evaluation Data 

In an operational environment, slap segmentation is required for ten-print cards 

and identification flats. Ten-print cards are synonymous with 2-inch data. 

Identification flats are synonymous with 3-inch data. Ten print cards contain right 

and left four finger slap images and plain impressions of each thumb in their own 

box. Identification flats contain right and left four finger slap images and a two 

finger slap that captures both thumbs in the same image. 

The segmentation process varies for 2-inch data and 3-inch data, due to the size 

of the image and number of components within the image. Because of the 

differences in the segmentation process, the SlapSegII test evaluates 

segmentation of both 2-inch data and 3-inch data as separate tests. Vendors are 

given the option to participate in only the 2-inch test, only the 3-inch test, or both. 

The 2-inch dataset is a random selection of law enforcement quality data with 

19,680 right slap images and 22,577 left slap images. There are 12,492 with both 

right and left slap images from the same person. The data is mainly of live-scan 

images with some scanned ink images. There is rotation in the images. 

The 3-inch segmentation evaluation uses randomly selected slap images from 

the Department of State identification flats. The 3-inch dataset contains 24,968 

right hand slaps, 24,964 left hand slaps, and 24,422 thumb slaps. There are 

24,377 cases that have all three slap images from the same person. The data 

contains only live-scan images. The fingerprints are assumed vertical with no 

rotation so there is no rotation of the segmentation boxes. 

5.1. Dataset Ground Truth 

The ground truth data is based on the NIST fingerprint segmentation algorithm 

(NFSEG.)[2] Humans examine every slap image starting with the NFSEG 

segmentation boxes and hand correct all errors producing the ground truth 

segmentation coordinates. The three main errors the examiners looked for were 

excess white space between a segmentation box edge and the fingerprint, a box 

side touching fingerprint ridges, and the bottom side correctly placed at the first 

crease. Figure 10 shows an example of ground truth segmentation boxes. 

The ground truth boxes are placed to capture only the part of the finger above 

the first joint (ie. the finger tip). The left, right, and top sides of the segmentation 

boxes are placed so that a small amount of white space exists between the 

segmentation box and the edges of the fingerprint. Ground truth information is 

included with validation data allowing users to see what is considered a “small 

amount of white space.” If two fingers are touching, the box sides are placed 

along the point of contact. 

The bottom side of the segmentation box is placed in the middle of the first 

joint/crease of the finger. If there is not a well defined white space at the crease, 

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19 
the box is still placed in the middle of the crease cutting through any ridge 

information that existed. If there is a slight slant in the fingerprint, (see 2nd print in 

Figure 10) the bottom side is placed to include the lowest part of the crease 

inside the segmentation box. Ground truth segmentation boxes do not extend 

past the edges of the slap image for 3-inch slap images, but corners can be 

outside the edge of the image for 2-inch data depending on rotation angle. 

After initial testing results were computed some ground truth data was reviewed 

as determined by statistical analysis to detect human errors. This included cases 

where all or almost all vendors miss the segmentation. 

Figure 10. Sample Ground Truth Boxes. 

5.2. Access to SlapSegII Test Data 

The SlapSegII Test datasets are protected under the Privacy Act (5 U.S.C. 

552a), and are treated as Controlled Unclassified Information (CUI) and/or Law 

Enforcement Sensitive. SlapSegII participants do not have access to SlapSegII 

test data, before, during, or after the test. 

6. SlapSegII Successful Segmentation Metric 

6.1. 3-inch Data 

The measure of a successful segmentation for the 3-inch dataset is a 

comparison of the segmentation algorithm’s output to hand marked ground truth 

coordinates determining if they are within an acceptable tolerance. The 

tolerances allowed are based on matching tests done with segmented slap 

image probes matched against a rolled gallery. A sample of segmented slap 

image data was selected from a dataset that also had rolled mates. Matching 

tests determined which tolerances around the hand-marked ground truth 

segmentation boxes had a minimal effect on matching results. The matchers 

used for this testing were matchers evaluated in the Proprietary Fingerprint 

Template evaluation (PFT)* http://fingerprint.nist.gov/PFT/index.html. 

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The baseline matching results were computed by matching the hand-marked 

ground truth segmented fingerprint images against the rolled fingerprint images. 

A matcher score threshold was chosen based on the baseline results and was 

fixed throughout the rest of the comparisons. 

Next each ground truth segmentation box was adjusted by various amounts and 

resulting segmentation images were matched against their rolled mates. These 

results were compared with the baseline results to determine how varying the 

edges of the ground truth segmentation box affect the number of False Rejects 

(FR) and False Accepts (FA) during matching. 

Figure 11 shows the averages for the various matching results and different 

segmentation tolerances across all the fingers from both hands. The first row in 

the table (“Ground Truth”) shows the number of false rejects and false accepts 

for the hand marked ground truth segmentation boxes. The “change from ground 

truth” columns show the difference between the number of FRs & FAs for a given 

tolerance adjustment and the ground truth value from the first row. The average 

number of mates (genuine) in the dataset was 9,300 and the average number of 

non-mates (imposters) was 36,713. The average size of the segmented images 

over the entire dataset was 270 pixels x 436 pixels. 

The “All sides” rows show results for varying all four sides at the same time at the 

given tolerance. These two rows show there is improvement in matcher 

performance when the size of the segmentation boxes increase beyond the size 

of the ground truth results. This allows the upper tolerance for the left, right, top 

and bottom to be set at +64 pixels. Since the crease is a difficult area to detect 

and the better matchers crop the input image during enrollment, the bottom 

tolerance allows +128 pixels over the ground truth bottom edge. 

The last 8 rows of the table show the effects of varying the left, right, top and 

bottom individually by -32 and -64 pixels. These results indicate a significantly 

larger error rate for both FR and FA using a -64 pixel change to the left or right 

sides. The top and bottom are tolerant to a change of -64 pixels. 

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Variation 

Average # 

False Reject 

Change from 

Ground Truth

Average # 

False Accept 

Change from 

Ground Truth

Ground Truth 77 24 

All Sides +32 68 -9 20 -4 

All Sides +64 62 -15 18 -6 

Left -32 86 9 34 10 

Left -64 97 20 64 40 

Right -32 87 10 37 13 

Right -64 103 26 64 40 

Top -32 78 1 25 1 

Top -64 81 4 33 9 

Bottom -32 80 3 27 3 

Bottom -64 88 11 32 8 

Figure 11. Matching results (number of FRs and FAs) for different 

segmentation box tolerances. 

The 3-inch successful segmentation is then computed for each finger in the slap 

image as follows (gt = ground truth): 

dleft = leftgt – left 

dright = right – rightgt

dtop = topgt – top 

dbottom = bottom – bottomgt

Successful segmentation of each finger is based on the following criteria: 

-32 <= dleft <= 64 

-32 <= dright <= 64 

-64 <= dtop <= 64 

-64 <= dbottom <= 128 

The image and table in Figure 12 show the segmentation tolerances for the 

left/right/top/bottom edges. The solid line box is the size of the “average” image 

at 270 x 436 pixels which at 500 dpi is 0.54 inches x 0.87 inches. All the boxes 

are adjusted by a factor of two for better viewing. 

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Lower 

Limits Upper 

Limits 

Side 

Segmentation Tolerances 

Lower Limit 

(pixels) 

Upper Limit 

(pixels) 

Left/Right -32 +64 

Top -64 +64 

Bottom -64 +128 

Figure 12. 3-inch Segmentation box tolerances. 

To further validate the choice of these segmentation box tolerances the NIST 

segmenter used in SlapSeg 04 was run on the data sample used to make Figure 

11 and scored against the hand marked ground truth coordinates using the 

tolerances previously discussed and shown in Figure 12. In SlapSeg04 the NIST 

segmenter was able to correctly segment 3 or more “matchable” fingers an 

average of 94.2% for slaps across the seven datasets used in that study [1]. 

Using this new metric for 3-inch data, the same segmenter can segment 3 or 

more fingers for 96.0% of the slap images. The reported results in section 7 use 

the tolerances shown in Figure 12 as the desired level of performance. 

6.2. 2-inch Data 

The measure of a successful segmentation for the 2-inch dataset is also a 

comparison of the segmentation algorithm’s output to hand marked ground truth 

coordinates determining if they are within an acceptable tolerance. The 

difference from the 3-inch slaps is the need to account for rotation in the 

segmentation boxes. Again, the segmentation tolerances were based on 

matching tests performed with segmented slap images matched to a rolled 

gallery. Tolerance values were selected so that segmentation would not 

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23 
significantly impact a fingerprint matcher’s performance when matching the 

segmented fingerprint. 

After trying several different methods of comparing segmentation output to 

ground truth for rotated data. An accurate and efficient method was developed to 

compare the four vertices (xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr) of the segmentation box to the 

ground truth vertices and determine if the segmentation vertices are within 

tolerances similar to those used with 3-inch data. The variations between the 

reported segmentation vertices and the ground truth are computed relative to the 

ground truth rotation angle as shown in Figure 14 and Figure 15 (picture on the 

left). The rotation angle reported by the segmentation algorithm is not used 

directly to determine successful segmentation but it is still being reported to 

assist in any error checking as needed. 

The acceptable distance tolerances for the vertices are set based on the 

matching done for the 3-inch slap data as described in the previous section 6.1. 

Additional matching was performed to determine the allowable rotation variance. 

Figure 13 shows the averages for the various matching results at different 

rotation variations across all the fingers for both hands. The first row in the table 

(“Ground Truth”) shows the number of false rejects and false accepts for the 

hand marked ground truth segmentation boxes. The “change from ground truth” 

columns show the difference between the number of FR & FA for a given rotation 

change (+/-5o

 through +/- 20o) and the ground truth rotation value. The average 

number of mates in the dataset was 9,300 and the average number of non-mates 

was 36,713. The average size of the segmented images over the entire dataset 

was 270 pixels x 436 pixels. 

The number of false rejects increased as the rotation angle was increasingly 

varied from the ground truth angle. It is interesting that the number of false 

accepts did not increase in a similar fashion. There is no definitive increase in the 

number of false rejects that defines a clear tolerance point. The conservative 

point is to allow +/- 5o

 from the ground truth angle. This coupled with the distance 

tolerances provides significant variation from ground truth boxes while still 

minimizing impact on the matcher. The chosen tolerance limits will also help 

preserve the ridge structure of the fingerprint for forensic purposes. 

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Variation 

Average # 

False Reject 

Change from 

Ground Truth

Average # 

False Accept 

Change from 

Ground Truth

Ground Truth 77 24 

Rotate 5o 80 3 31 7 

Rotate -5o 79 2 28 4 

Rotate 10o 82 5 30 6 

Rotate -10o 82 5 29 5 

Rotate 15o 84 7 30 6 

Rotate -15o 84 7 29 5 

Rotate 20o 85 8 30 6 

Rotate -20o 87 10 29 5 

Figure 13. Matching results (number of FRs and FAs) for different 

segmentation box rotation tolerances. 

For 2-inch data the reported segmentation vertices are compared to the ground 

truth vertices relative to the ground truth angle (varied by +/-5o). If the reported 

segmentation vertices are within tolerance at any of the three angles {-5o

, 0o, +5o} 

then they are accepted as a successful segmentation. This could mean that the 

top-left corner is within tolerance at thetagt+5 o and the bottom-right corner is 

within tolerance at thetagt-5 o and the segmentation box is still considered good. 

The differences between the four vertices returned by the segmentation 

algorithm (xtl,ytl,xtr,ytr,xbl,ybl,xbr,ybr) and the ground truth (gt) vertices are computed 

for each fingerprint in the slap image as follows (Figure 14 is a drawing of the 

parameter placement for the top-left corner): 

dx1tl = xtl - xtlgt

dx1tr = xtrgt - xtr

dx1bl = xbl - xblgt

dx1br = xbrgt - xbr

dy1tl = ytl - ytlgt

dy1tr = ytr - ytrgt

dy1bl = yblgt - ybl

dy1br = ybrgt - ybr 

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dtl = sqrt(((dx1tl)**2) + ((dy1tl)**2)) 

dtr = sqrt(((dx1tr)**2) + ((dy1tr)**2)) 

dbl = sqrt(((dx1bl)**2) + ((dy1bl)**2)) 

dbr = sqrt(((dx1br)**2) + ((dy1br)**2)) 

theta1tl = tan-1(dy1tl/dx1tl) 

theta1tr = tan-1(dy1tr/dx1tr) 

theta1bl = tan-1(dy1bl/dx1bl) 

theta1br = tan-1(dy1br/dx1br) 

thetatl = theta1tl + thetagt

thetatr = theta1tr - thetagt

thetabl = theta1bl - thetagt 

thetabr = theta1br + thetagt

dxtl = int(dtl * cos(thetatl) + 0.5) 

dytl = int(dtl * sin(thetatl) + 0.5) 

dxtr = int(dtr * cos(thetatr) + 0.5) 

dytr = int(dtr * sin(thetatr) + 0.5) 

dxbl = int(dbl * cos(thetabl) + 0.5) 

dybl = int(dbl * sin(thetabl) + 0.5) 

dxbr = int(dbr * cos(thetabr) + 0.5) 

dybr = int(dbr * sin(thetabr) + 0.5) 

These computations are repeated for thetagt-5o

 and thetagt+5o and successful 

segmentation is based on the difference values for any of the three angles 

thetagt, thetagt-5o

 or thetagt+5o meeting the following criteria: 

-32 <= {dxtl, dxtr} <= 64 

-32 <= {dxbl, dxbr} <= 64 

-64 <= {dytl, dytr} <= 64 

-64 <= {dybl, dybr} <= 128 

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Figure 14. Shows the parameter placement (top-left corner) when 

computing the success measure for 2-inch segmentation boxes (this 

drawing is not to scale it is just intended to assist in understanding the 

formulas in section 6.2). 

The images and table in Figure 15 show the segmentation tolerances allowed for 

2-inch slap data. The solid line box is the size of the “average” image at 270 x 

436 pixels which at 500 dpi is 0.54 inches x 0.87 inches and shown at a rotation 

angle of -20o (image on the left). All the boxes are adjusted by a factor of two for 

better viewing. The “acceptable tolerance” box for each corner point is shown by 

the dotted line also rotated relative to the ground truth angle of rotation (-20o for 

this example). The image on the right in Figure 15 shows the distance tolerances 

at +/-5o

 from the ground truth angle of -20o. Again, for successful segmentation 

all four vertices must be within tolerance at any of the three angular positions. 

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-20o

-5o

, 0o, +5o

Side 

Segmentation Tolerances 

Lower Limit 

(pixels) 

Upper Limit (pixels) 

X-limits (dx) -32 +64 

Top Y-Limits (dy) -64 +64 

Bottom Y-Limits (dy) -64 +128 

Rotation -5 degrees +5 degrees 

Figure 15. 2-inch segmentation tolerances. 

To further validate the choice of these segmentation box tolerances the NIST 

segmenter that was used in SlapSeg 04 was run on the data sample used to 

make Figure 13 and scored against the hand marked ground truth coordinates 

using the tolerances previously discussed and shown in Figure 15. In SlapSeg04 

the NIST segmenter was able to correctly segment 3 or more “matchable” fingers 

an average of 94.2% for slaps across the seven datasets used in that study [1]. 

Using this new metric for 2-inch data, the same segmenter can segment 3 more 

fingers for 93.7% of the slap images. The 2-inch results reported in section 7 use 

the tolerances shown in Figure 15 as the desired level of performance. 

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7. Results 

A summary of some key results are given in this section but all the tables and 

plots generated while analyzing the slap segmentation results are included in 

appendices at the end of the document. The appendices are: 

Appendix A. Result tables for 3-inch slap images. 

Appendix B. Result tables for 2-inch slap images. 

Appendix C. Detailed segmentation statistics. 

Appendix D. Plots of 3-inch segmentation box centers. 

Appendix E. Plots of 3-inch segmentation box widths and heights. 

Appendix F. Plots of 2-inch segmentation box centers. 

Appendix G. Plots of 2-inch segmentation box widths and heights. 

Appendix H. Confidence intervals for 3-inch segmentation results. 

Appendix I. Confidence intervals for 2-inch segmentation results. 

The sample size for the 2-inch dataset is 19,680 right and 22,577 left slap 

images. There are 12,492 cases that have both the left and right hand from the 

same person. The sample size for the 3-inch dataset is 24,968 right, 24,964 left 

and 24,422 thumb slap images. There are 24,377 cases that have all three slap 

images from the same person. 

Correct segmentation for SlapSegII means that the segmentation coordinates 

returned by the algorithm are both within the tolerance limits specified in section 

6 and that the correct fingerprint position is reported in the output file as 

described in section 4.9.1. 

The results from SlapSegII show there are many segmentation algorithms 

capable of segmenting fingerprints successfully while preserving the majority of 

the fingerprint ridge structure. Table 1 shows the successful segmentation rates 

for 3-inch data for both right and left hands. The columns show percentages for 

correctly segmenting all 5 finger positions, any 4, any 3, all the way to none. The 

majority of algorithms are able to correctly segment any 4 fingers for 95-99% of 

the slaps. This is a very encouraging result. Table 2 shows the same type of 

results but only using the right and left four finger slaps (no thumbs) and again a 

majority of algorithms correctly segment any 3 fingers for 96-99% of the slap 

images. Table 3 shows the results by person with columns for correctly 

segmenting all 10 fingers all the way to none. Most algorithms were able to 

correctly segment any 6 fingers for 99% of the cases. Figure 16 and Figure 17

are plots of the right hand results from Table 1 and similar plots for the other 

results are available in Appendix H. 

A second set of results are listed for segmentation algorithm A (A+32) where 

original segmentation points are adjusted by adding 32 to all the values returned. 

This was done after analyzing the statistics tables shown in Appendix C. The 

table showed a significant # of errors below the minimum threshold and a 

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29 
tendency for the algorithm to crop into the fingerprint image which was confirmed 

by visual inspection on a sample of the test data. This +32 adjustment 

significantly increased the performance of the algorithm which is clearly shown in 

the (A+32) results. 

Algorithm J had significant problems with the fingerprint crease, specifically 

“overshooting” the crease. If the maximum limit on the crease is ignored, as 

shown in the “JBmx” row and in the “B” and “C” tables in Appendix A, there is a 

significant jump in performance for this algorithm. 

Right Hand Left Hand

All 5 Any 4 Any 3 Any 2 Any 1 None All 5 Any 4 Any 3 Any 2 Any 1 None

A 6.70 27.32 54.86 79.08 93.95 6.05 15.78 44.59 69.50 86.92 96.70 3.30

A+32 54.00 83.44 93.44 97.16 99.45 0.55 62.37 87.22 94.37 97.32 99.49 0.51

B 93.76 99.45 99.84 99.96 100.00 0.00 94.37 99.46 99.83 99.94 100.00 0.00

C 94.28 99.62 99.93 99.97 100.00 0.00 94.71 99.59 99.93 99.97 100.00 0.00

D 72.53 95.16 98.55 99.40 99.95 0.05 72.13 95.17 98.80 99.75 99.97 0.03

E 82.91 95.41 98.33 99.35 99.98 0.02 79.67 94.17 97.97 99.24 99.92 0.08

F 86.98 96.98 98.59 99.37 99.96 0.04 85.57 96.21 98.53 99.32 99.95 0.05

G 87.65 98.94 99.77 99.92 100.00 0.00 85.39 98.70 99.80 99.95 99.99 0.01

H 69.73 96.02 99.12 99.73 99.94 0.06 73.99 96.15 99.00 99.60 99.93 0.07

I 81.80 96.80 99.15 99.73 99.93 0.07 78.15 96.87 99.13 99.70 99.94 0.06

J 10.47 25.88 45.17 72.01 94.91 5.09 10.05 25.33 43.67 69.48 93.61 6.39

JBmx 64.91 90.22 96.90 98.81 99.79 0.21 63.22 88.76 95.24 97.04 99.61 0.39

Table 1. 3-inch segmentation results for right and left hands including 

thumbs. 

Right Hand Left Hand

All 4 Any 3 Any 2 Any 1 None All 4 Any 3 Any 2 Any 1 None

A 15.83 43.58 71.95 90.80 9.20 28.03 58.14 80.04 93.33 6.67

A+32 66.57 88.17 95.19 97.92 2.08 73.60 90.21 95.38 97.79 2.21

B 95.58 99.55 99.84 99.96 0.04 95.99 99.56 99.85 99.94 0.06

C 97.34 99.80 99.96 99.98 0.02 97.15 99.76 99.94 99.97 0.03

D 85.13 96.53 98.82 99.47 0.53 85.22 96.62 99.10 99.82 0.18

E 86.58 96.18 98.53 99.49 0.51 84.84 95.33 98.35 99.40 0.60

F 90.63 97.30 98.69 99.41 0.59 89.33 96.77 98.65 99.36 0.64

G 94.89 99.32 99.85 99.96 0.04 94.08 99.15 99.86 99.97 0.03

H 90.21 98.40 99.57 99.82 0.18 88.36 98.12 99.40 99.70 0.30

I 88.77 97.79 99.34 99.78 0.22 90.02 98.00 99.33 99.79 0.21

J 13.27 28.76 48.75 78.34 21.66 12.45 28.29 47.19 75.95 24.05

JBmx 74.72 92.78 97.71 99.18 0.82 72.68 91.26 95.87 97.32 2.68

Table 2. 3-inch segmentation results for right and left hands excluding 

thumbs. 

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30 
Person

All 10 Any 9 Any 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 1.80 8.20 20.86 37.93 56.65 73.22 85.82 93.53 97.80 99.58 0.42

A+32 39.50 65.52 82.08 90.30 95.07 97.56 98.93 99.51 99.85 99.95 0.05

B 89.32 98.04 99.49 99.84 99.95 99.98 99.99 100.00 100.00 100.00 0.00

C 90.21 98.30 99.66 99.89 99.96 99.99 100.00 100.00 100.00 100.00 0.00

D 58.02 82.00 94.47 97.96 99.29 99.76 99.92 99.98 100.00 100.00 0.00

E 70.14 87.37 94.17 97.23 98.93 99.47 99.76 99.92 99.99 100.00 0.00

F 76.52 91.69 96.19 98.17 99.43 99.73 99.83 99.93 100.00 100.00 0.00

G 78.09 93.50 99.02 99.68 99.89 99.95 99.98 100.00 100.00 100.00 0.00

H 59.90 81.10 95.20 98.22 99.35 99.68 99.89 99.93 99.97 99.99 0.01

I 66.65 89.93 96.74 98.78 99.50 99.78 99.89 99.95 99.98 100.00 0.00

J 3.95 10.33 18.61 28.02 38.72 51.25 66.21 81.58 93.69 98.22 1.78

JBmx 47.20 73.00 87.20 93.21 96.71 98.36 99.28 99.68 99.89 99.96 0.04

Table 3. 3-inch segmentation results for all ten fingers. 

Figure 16. 3-inch segmentation results for right hand including thumbs. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

31 
Figure 17. Same results as Figure 16 with scale 90-100% correct. 

Appendix A shows all the results for 3-inch data by individual finger position and 

various finger combinations. A major result for the 3-inch data is that the thumbs 

cause the most problems for the segmentation algorithms as shown in Table 4. 

This is most likely a result of the “two thumb” slap image being the newest type of 

slap image. Most certainly algorithms will be able to adjust for this newer image 

type and improve overall accuracy in the not too distant future. Issues that exist 

with these “two thumb” slaps are the lack of “finger position geometry” and a 

higher frequency of users rotating their thumbs outward. As the thumbs are put 

on the platen together the tips are generally at the same vertical position, unlike 

the four finger slaps where the fingers are spread at “logical” positions in the 

image which can be used to improve confidence/accuracy in segmentation. 

There is also a problem with users rotating the bottom of their thumbs outward 

during image capture. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

32 
Finger Position

RT RI RM RR RL LT LI LM LR LL

A 39.79 68.76 61.73 47.38 44.26 53.85 56.58 64.50 67.84 70.71

A+32 79.46 93.36 87.30 84.10 83.28 83.32 91.62 87.92 87.95 89.95

B 97.99 99.22 98.79 98.31 98.69 98.11 99.08 98.88 98.62 98.92

C 96.68 99.58 99.31 98.88 99.35 97.27 99.55 99.14 98.95 99.29

D 85.31 96.20 94.92 93.99 95.16 84.74 96.05 95.00 94.98 95.05

E 94.77 95.41 94.67 94.86 96.27 92.56 95.18 93.73 94.35 95.16

F 95.55 96.10 96.25 96.53 97.44 95.09 95.97 95.49 96.19 96.84

G 92.19 99.02 98.62 98.13 98.31 90.68 98.51 98.17 98.29 98.17

H 76.35 98.22 97.38 97.11 95.48 82.85 97.62 97.11 97.07 94.01

I 91.66 97.55 96.82 96.21 95.16 86.40 97.89 96.89 96.50 96.12

J 78.36 38.18 39.15 36.60 56.15 77.08 33.12 38.83 38.80 54.32

Table 4. 3-inch segmentation results by finger position. 

Table 5 shows the right and left hand results for the 2-inch slap images. Again, 

there are columns for correctly segmenting all 4, any 3, any 2, any 1 and none of 

the finger positions. These results are also very positive as most segmentation 

algorithms were able to segment any 3 of the finger positions around 96-99% 

correct for both the right and left hands. Performance is off slightly for getting all 

4 finger positions ranging from 83-94% correct segmentations. Ignoring the 

crease pushes the numbers up to 86-96% correct segmentation. Table 6 shows 

results by person with columns for “All 8” down to “None.” Most algorithms were 

able to correctly segment “Any 6” fingers for 95-99% of the cases. 

Right Hand Left Hand

All 4

Any

3

Any

2

Any

1 None All 4

Any

3

Any

2

Any

1 None

A 18.63 40.34 60.00 78.02 21.98 19.30 41.46 59.98 77.37 22.63

A+32 64.09 86.20 94.41 97.74 2.26 66.06 86.35 94.13 97.77 2.23

B 91.05 97.70 98.88 99.46 0.54 90.31 97.54 98.80 99.43 0.57

C 94.01 98.76 99.45 99.73 0.27 94.67 99.01 99.57 99.81 0.19

E 92.98 99.31 99.80 99.95 0.05 91.71 98.80 99.70 99.88 0.12

F 93.12 99.36 99.79 99.92 0.08 93.34 99.18 99.80 99.89 0.11

G 89.62 97.48 98.99 99.57 0.43 90.03 96.94 98.58 99.27 0.73

H 83.12 96.85 99.09 99.59 0.41 83.78 96.16 98.52 99.16 0.84

I 89.19 97.03 98.48 99.15 0.85 88.58 96.92 98.53 99.24 0.76

J 24.96 49.96 71.08 87.31 12.69 21.76 46.95 69.50 87.81 12.19

JBmx 56.44 76.14 84.77 90.90 9.10 64.24 79.60 86.79 91.65 8.35

Table 5. 2-inch segmentation results for right and left hands. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

33 
Person

All 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 4.86 13.54 25.01 39.39 57.06 73.05 84.81 93.94 6.06

A+32 43.79 68.15 81.47 89.33 95.18 97.93 99.25 99.76 0.24

B 83.43 94.89 97.35 98.53 99.67 99.91 99.96 99.98 0.02

C 89.57 97.36 98.82 99.47 99.92 99.98 99.98 99.99 0.01

E 85.12 96.81 99.15 99.74 99.94 100.00 100.00 100.00 0.00

F 87.30 97.97 99.48 99.80 99.98 100.00 100.00 100.00 0.00

G 81.56 93.47 96.85 98.31 99.44 99.73 99.88 99.94 0.06

H 70.97 90.67 96.15 97.93 98.98 99.46 99.62 99.77 0.23

I 79.50 92.98 96.39 98.00 99.58 99.84 99.90 99.94 0.06

J 8.60 22.37 37.59 52.58 68.04 80.35 91.07 96.37 3.63

JBmx 41.98 61.33 72.27 80.23 89.66 93.76 96.37 97.84 2.16

Table 6. 2-inch segmentation results for all eight fingers. 

Appendix B shows 2-inch data results for individual and combinations of finger 

positions. A little unexpected is how well the algorithms are able to correctly 

segment the “little” finger positions. 

The scatter plots in Appendix D - Appendix G are useful visual aids for 

comparing the segmentation algorithm’s detected fingerprint locations and size. 

The locations and sizes are included for the ground truth allowing visual 

comparisons. As a good example, the 3-inch thumb plots for algorithm H are 

shown in Figure 18 and clearly show that some right thumbs are being marked 

as left thumbs. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

34 
Figure 18. Scatter plot of algorithm H’s segmentation center (x,y) position 

for 3-inch “two-thumb” slaps. 

8. Future Work 

Future work that has already started is evaluating the effects segmentation has 

on matching for the 2-inch slap dataset. Specifically, what affect does cropping of 

the segmented slap have on fingerprint matching performance? This particular 

dataset has rolled mates that can be used for matching. This is an extension of 

the matching work that was performed in section 6 when determining the 

segmentation tolerances used in the current performance metrics. Now the 

matching results of the ground truth segmentation boxes can be compared to the 

matching results of each segmentation algorithm and see how much, if any, 

difference occurs. These results will help study the impact of the segmentation 

process on the matching performance of an AFIS. 

Other analysis might look at the success of segmentation on low quality slap 

images, images with “ghost” images present, or the affect of segmentation on 

fingerprint pattern classification. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

35 
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

36 

9. References 

1. Slap Fingerprint Segmentation Evaluation 2004 (SlapSeg04). NISTIR 7209. 

http://fingerprint.nist.gov/SlapSeg04

2. NIST Biometric Image Software, http://biometrics.nist.gov/nigos

3. “American National Standard for Information Systems – Data Format for the 

Interchange of Fingerprint, Facial, & Other Biometric Information – Part 1,” 

ANSI/NIST-ITL 1-2007, NIST Special Publication 500-271, May 2007. 

http://fingerprint.nist.gov/standard/index.html
Appendix A. Result tables for 3-inch slap images. 

This appendix shows successful segmentation rates for the 3-inch slap images 

by finger position, hand, and various combinations of fingers that may be of 

interest to different fingerprint matching applications. 

The first table shows successful segmentation percentages for each finger 

position. 

The second table combines the right and left hand for each finger position and 

shows results for getting both the right and left finger, either or none. 

The third table looks at the results by right and left hand. Columns show 

segmentation rates for correctly segmenting all 5 finger positions, any 4, any 3, 

down to none. 

The fourth table is similar to the third table but only uses the four finger slaps, no 

thumbs. 

The fifth table is shows results for all ten fingers by combining right and left 

hands. 

The last three tables show results for finger position combinations of 

thumb/index, thumb/index/middle and index/middle/ring. 

All eight tables are then repeated (B) for the case where the maximum limited of 

the bottom (+128) is ignored and then repeated (C) again ignoring the bottom 

(crease) completely. This was done because previous work had shown the 

crease is usually the most difficult edge for the segmentation algorithm to detect 

and in general this how much the crease detection affects the success rate of the 

segmentation algorithm. The results in these tables show algorithm J definitely 

had difficulty detecting the crease and many other algorithms show significant 

increases in successfully segmenting “All 5” finger positions on a hand when the 

crease is ignored. Again, this is not a surprise as detecting the correct crease is a 

known difficulty for segmentation algorithms. 

Most of the increase in segmentation performance comes from ignoring the 

maximum limit (+128) which will probably have less effect on matching but 

requires keeping/processing more of the slap fingerprint. This larger fingerprint 

area could have a detrimental effect on processing speeds for large scale 

systems, with no gain in system accuracy. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
L/R -32/+64, T -64/+64, B -64/+128

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐1

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐1

Finger Position

RT RI RM RR RL LT LI LM LR LL

A 39.79 68.76 61.73 47.38 44.26 53.85 56.58 64.50 67.84 70.71

A+32 79.46 93.36 87.30 84.10 83.28 83.32 91.62 87.92 87.95 89.95

B 97.99 99.22 98.79 98.31 98.69 98.11 99.08 98.88 98.62 98.92

C 96.68 99.58 99.31 98.88 99.35 97.27 99.55 99.14 98.95 99.29

D 85.31 96.20 94.92 93.99 95.16 84.74 96.05 95.00 94.98 95.05

E 94.77 95.41 94.67 94.86 96.27 92.56 95.18 93.73 94.35 95.16

F 95.55 96.10 96.25 96.53 97.44 95.09 95.97 95.49 96.19 96.84

G 92.19 99.02 98.62 98.13 98.31 90.68 98.51 98.17 98.29 98.17

H 76.35 98.22 97.38 97.11 95.48 82.85 97.62 97.11 97.07 94.01

I 91.66 97.55 96.82 96.21 95.16 86.40 97.89 96.89 96.50 96.12

J 78.36 38.18 39.15 36.60 56.15 77.08 33.12 38.83 38.80 54.32

Thumb Index Middle Ring Little

Both Either None Both Either None Both Either None Both Either None Both Either None

A 27.21 66.42 33.58 39.87 85.47 14.53 41.33 84.90 15.10 33.74 81.48 18.52 32.51 82.46 17.54

A+32 72.54 90.24 9.76 86.20 98.79 1.21 78.16 97.05 2.95 75.26 96.78 3.22 76.04 97.19 2.81

B 96.48 99.63 0.37 98.33 99.96 0.04 97.76 99.90 0.10 97.08 99.85 0.15 97.69 99.92 0.08

C 94.63 99.32 0.68 99.14 99.99 0.01 98.52 99.93 0.07 97.97 99.86 0.14 98.67 99.97 0.03

D 78.01 92.04 7.96 92.70 99.54 0.46 90.91 99.01 0.99 89.94 99.04 0.96 90.85 99.36 0.64

E 89.42 97.91 2.09 91.34 99.24 0.76 89.65 98.74 1.26 90.50 98.71 1.29 92.15 99.28 0.72

F 91.74 98.90 1.10 92.62 99.46 0.54 92.32 99.42 0.58 93.24 99.48 0.52 94.63 99.65 0.35

G 86.71 96.16 3.84 97.60 99.94 0.06 96.94 99.84 0.16 96.58 99.84 0.16 96.57 99.91 0.09

H 71.80 87.40 12.60 96.02 99.81 0.19 94.92 99.57 0.43 94.63 99.55 0.45 90.20 99.29 0.71

I 80.95 97.10 2.90 95.64 99.79 0.21 94.09 99.61 0.39 93.30 99.41 0.59 91.89 99.39 0.61

J 67.69 87.75 12.25 21.47 49.82 50.18 25.85 52.12 47.88 23.99 51.41 48.59 36.62 73.85 26.15

Right Hand (w/Thumbs) Left Hand (w/Thumbs)

All 5 Any 4 Any 3 Any 2 Any 1 None All 5 Any 4 Any 3 Any 2 Any 1 None

A 6.70 27.32 54.86 79.08 93.95 6.05 15.78 44.59 69.50 86.92 96.70 3.30

A+32 54.00 83.44 93.44 97.16 99.45 0.55 62.37 87.22 94.37 97.32 99.49 0.51

B 93.76 99.45 99.84 99.96 100.00 0.00 94.37 99.46 99.83 99.94 100.00 0.00

C 94.28 99.62 99.93 99.97 100.00 0.00 94.71 99.59 99.93 99.97 100.00 0.00

D 72.53 95.16 98.55 99.40 99.95 0.05 72.13 95.17 98.80 99.75 99.97 0.03

E 82.91 95.41 98.33 99.35 99.98 0.02 79.67 94.17 97.97 99.24 99.92 0.08

F 86.98 96.98 98.59 99.37 99.96 0.04 85.57 96.21 98.53 99.32 99.95 0.05

G 87.65 98.94 99.77 99.92 100.00 0.00 85.39 98.70 99.80 99.95 99.99 0.01

H 69.73 96.02 99.12 99.73 99.94 0.06 73.99 96.15 99.00 99.60 99.93 0.07

I 81.80 96.80 99.15 99.73 99.93 0.07 78.15 96.87 99.13 99.70 99.94 0.06

J 10.47 25.88 45.17 72.01 94.91 5.09 10.05 25.33 43.67 69.48 93.61 6.39

Right Hand Left Hand

All 4 Any 3 Any 2 Any 1 None All 4 Any 3 Any 2 Any 1 None

A 15.83 43.58 71.95 90.80 9.20 28.03 58.14 80.04 93.33 6.67

A+32 66.57 88.17 95.19 97.92 2.08 73.60 90.21 95.38 97.79 2.21

B 95.58 99.55 99.84 99.96 0.04 95.99 99.56 99.85 99.94 0.06

C 97.34 99.80 99.96 99.98 0.02 97.15 99.76 99.94 99.97 0.03

D 85.13 96.53 98.82 99.47 0.53 85.22 96.62 99.10 99.82 0.18

E 86.58 96.18 98.53 99.49 0.51 84.84 95.33 98.35 99.40 0.60

F 90.63 97.30 98.69 99.41 0.59 89.33 96.77 98.65 99.36 0.64

G 94.89 99.32 99.85 99.96 0.04 94.08 99.15 99.86 99.97 0.03

H 90.21 98.40 99.57 99.82 0.18 88.36 98.12 99.40 99.70 0.30

I 88.77 97.79 99.34 99.78 0.22 90.02 98.00 99.33 99.79 0.21

J 13.27 28.76 48.75 78.34 21.66 12.45 28.29 47.19 75.95 24.05
L/R -32/+64, T -64/+64, B -64/+128

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐2

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐2

Person

All 10 Any 9 Any 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 1.80 8.20 20.86 37.93 56.65 73.22 85.82 93.53 97.80 99.58 0.42

A+32 39.50 65.52 82.08 90.30 95.07 97.56 98.93 99.51 99.85 99.95 0.05

B 89.32 98.04 99.49 99.84 99.95 99.98 99.99 100.00 100.00 100.00 0.00

C 90.21 98.30 99.66 99.89 99.96 99.99 100.00 100.00 100.00 100.00 0.00

D 58.02 82.00 94.47 97.96 99.29 99.76 99.92 99.98 100.00 100.00 0.00

E 70.14 87.37 94.17 97.23 98.93 99.47 99.76 99.92 99.99 100.00 0.00

F 76.52 91.69 96.19 98.17 99.43 99.73 99.83 99.93 100.00 100.00 0.00

G 78.09 93.50 99.02 99.68 99.89 99.95 99.98 100.00 100.00 100.00 0.00

H 59.90 81.10 95.20 98.22 99.35 99.68 99.89 99.93 99.97 99.99 0.01

I 66.65 89.93 96.74 98.78 99.50 99.78 99.89 99.95 99.98 100.00 0.00

J 3.95 10.33 18.61 28.02 38.72 51.25 66.21 81.58 93.69 98.22 1.78

Right Thumb/Index Left Thumb/Index

Both Either None Both Either None

A 28.02 80.53 19.47 31.20 79.23 20.77

A+32 74.61 98.21 1.79 76.70 98.24 1.76

B 97.25 99.97 0.03 97.24 99.95 0.05

C 96.32 99.95 0.05 96.88 99.94 0.06

D 82.00 99.51 0.49 81.34 99.45 0.55

E 90.66 99.52 0.48 88.44 99.29 0.71

F 91.91 99.75 0.25 91.39 99.67 0.33

G 91.32 99.89 0.11 89.33 99.86 0.14

H 75.28 99.29 0.71 81.14 99.33 0.67

I 89.56 99.65 0.35 84.71 99.57 0.43

J 30.02 86.51 13.49 26.03 84.17 15.83

Right Thumb/Index/Middle Left Thumb/Index/Middle

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 19.41 61.28 89.59 10.41 23.30 61.93 89.69 10.31

A+32 67.82 93.28 99.02 0.98 70.33 93.49 99.04 0.96

B 96.20 99.81 99.99 0.01 96.32 99.77 99.98 0.02

C 95.72 99.86 99.99 0.01 96.13 99.85 99.98 0.02

D 78.71 97.86 99.85 0.15 77.89 98.06 99.84 0.16

E 87.58 97.46 99.81 0.19 84.87 96.90 99.70 0.30

F 89.99 98.02 99.89 0.11 88.97 97.72 99.86 0.14

G 90.27 99.61 99.96 0.04 87.83 99.57 99.96 0.04

H 73.92 98.24 99.79 0.21 79.37 98.40 99.82 0.18

I 87.38 98.78 99.86 0.14 82.61 98.71 99.85 0.15

J 19.25 47.11 89.33 10.67 17.72 43.79 87.51 12.49

Right Index/Middle/Ring Left Index/Middle/Ring

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 27.47 62.64 87.76 12.24 33.73 66.94 88.25 11.75

A+32 75.36 92.32 97.08 2.92 78.19 92.47 96.83 3.17

B 96.70 99.67 99.94 0.06 96.96 99.72 99.90 0.10

C 97.95 99.86 99.96 0.04 97.84 99.83 99.97 0.03

D 88.59 97.44 99.08 0.92 88.82 97.76 99.44 0.56

E 89.10 96.90 98.93 1.07 87.94 96.44 98.88 1.12

F 92.35 97.66 98.88 1.12 91.33 97.37 98.95 1.05

G 96.37 99.50 99.92 0.08 95.60 99.43 99.93 0.07

H 93.99 99.00 99.72 0.28 93.31 98.84 99.66 0.34

I 92.53 98.47 99.57 0.43 93.11 98.58 99.59 0.41

J 18.18 36.08 59.67 40.33 17.38 35.49 57.87 42.13
(B) Crease Maximum Limit Ignored

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐3

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐3

Finger Position

RT RI RM RR RL LT LI LM LR LL

A 40.77 70.16 63.23 48.60 45.70 54.99 58.24 66.31 69.60 72.52

A+32 81.33 95.04 89.61 85.79 85.05 85.70 93.67 90.57 90.40 91.69

B 98.30 99.49 99.25 98.87 98.89 98.48 99.22 99.23 98.84 99.11

C 96.81 99.75 99.58 99.22 99.48 97.45 99.65 99.50 99.17 99.50

D 85.72 98.03 97.95 97.14 96.67 85.26 97.53 98.02 97.88 96.82

E 98.08 97.21 97.25 97.90 98.13 98.06 97.05 96.62 97.51 97.49

F 97.28 96.99 96.88 97.59 98.14 97.37 96.88 96.21 97.40 97.60

G 95.22 99.11 98.78 98.32 98.50 95.36 98.58 98.36 98.48 98.40

H 77.20 98.36 97.81 97.85 96.37 84.06 97.78 97.44 97.78 95.04

I 92.42 98.52 98.41 98.26 95.55 87.34 98.82 98.20 98.30 96.48

J 85.72 91.84 94.46 91.36 87.25 86.13 87.73 92.59 90.22 87.20

Thumb Index Middle Ring Little

Both Either None Both Either None Both Either None Both Either None Both Either None

A 28.38 67.38 32.62 41.65 86.76 13.24 43.11 86.43 13.57 35.28 82.93 17.07 34.35 83.87 16.13

A+32 75.65 91.37 8.63 89.40 99.32 0.68 82.09 98.09 1.91 78.57 97.62 2.38 78.94 97.79 2.21

B 97.10 99.67 0.33 98.75 99.96 0.04 98.55 99.93 0.07 97.84 99.87 0.13 98.06 99.93 0.07

C 94.91 99.35 0.65 99.41 99.99 0.01 99.11 99.97 0.03 98.49 99.90 0.10 99.00 99.98 0.02

D 78.85 92.13 7.87 95.67 99.89 0.11 96.15 99.82 0.18 95.24 99.77 0.23 93.81 99.68 0.32

E 96.52 99.62 0.38 94.56 99.70 0.30 94.25 99.62 0.38 95.73 99.69 0.31 95.87 99.75 0.25

F 95.22 99.43 0.57 94.26 99.61 0.39 93.49 99.61 0.39 95.27 99.72 0.28 95.98 99.76 0.24

G 92.59 97.99 2.01 97.74 99.94 0.06 97.27 99.87 0.13 96.93 99.87 0.13 96.98 99.92 0.08

H 73.38 87.87 12.13 96.31 99.84 0.16 95.64 99.61 0.39 95.94 99.69 0.31 91.93 99.48 0.52

I 82.11 97.65 2.35 97.44 99.90 0.10 96.80 99.82 0.18 96.74 99.82 0.18 92.55 99.47 0.53

J 79.32 92.52 7.48 81.83 97.74 2.26 88.19 98.86 1.14 83.75 97.83 2.17 77.79 96.66 3.34

Right Hand (w/Thumbs) Left Hand (w/Thumbs)

All 5 Any 4 Any 3 Any 2 Any 1 None All 5 Any 4 Any 3 Any 2 Any 1 None

A 7.33 29.19 56.87 80.52 94.56 5.44 17.00 46.90 71.83 88.62 97.32 2.68

A+32 57.90 86.20 95.04 98.03 99.64 0.36 67.11 90.31 96.41 98.48 99.73 0.27

B 95.36 99.62 99.86 99.96 100.00 0.00 95.55 99.54 99.85 99.95 100.00 0.00

C 95.26 99.67 99.94 99.97 100.00 0.00 95.67 99.69 99.93 99.97 100.00 0.00

D 79.80 97.37 98.94 99.45 99.95 0.05 78.90 97.53 99.30 99.82 99.98 0.02

E 92.23 97.90 98.96 99.51 99.98 0.02 90.93 97.47 98.85 99.50 99.99 0.01

F 91.14 97.65 98.74 99.38 99.98 0.02 90.06 97.29 98.75 99.38 99.99 0.01

G 91.07 99.15 99.78 99.93 100.00 0.00 90.40 99.01 99.83 99.95 99.99 0.01

H 71.87 96.80 99.24 99.74 99.94 0.06 76.57 96.89 99.12 99.61 99.93 0.07

I 85.61 98.26 99.54 99.81 99.94 0.06 81.64 98.17 99.56 99.82 99.95 0.05

J 64.91 90.22 96.90 98.81 99.79 0.21 63.22 88.76 95.24 97.04 99.61 0.39

Right Hand Left Hand

All 4 Any 3 Any 2 Any 1 None All 4 Any 3 Any 2 Any 1 None

A 17.11 45.59 73.45 91.65 8.35 29.84 60.42 82.01 94.41 5.59

A+32 69.85 90.32 96.58 98.63 1.37 77.37 92.63 97.20 98.79 1.21

B 96.93 99.70 99.86 99.96 0.04 96.88 99.62 99.86 99.95 0.05

C 98.25 99.84 99.96 99.98 0.02 98.02 99.82 99.94 99.97 0.03

D 92.85 98.25 99.11 99.50 0.50 92.32 98.45 99.45 99.86 0.14

E 93.89 98.00 98.95 99.52 0.48 92.42 97.61 98.90 99.49 0.51

F 93.51 97.77 98.77 99.41 0.59 92.18 97.48 98.79 99.38 0.62

G 95.47 99.37 99.86 99.96 0.04 94.68 99.24 99.86 99.97 0.03

H 92.15 98.69 99.60 99.82 0.18 90.28 98.43 99.44 99.70 0.30

I 92.31 98.93 99.64 99.84 0.16 93.10 98.97 99.66 99.88 0.12

J 74.72 92.78 97.71 99.18 0.82 72.68 91.26 95.87 97.32 2.68
(B) Crease Maximum Limit Ignored

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐4

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐4

Person

All 10 Any 9 Any 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 2.07 9.16 22.57 40.56 59.65 75.80 87.62 94.67 98.34 99.70 0.30

A+32 44.53 70.65 86.17 93.16 96.69 98.55 99.42 99.76 99.93 99.99 0.01

B 91.81 98.50 99.57 99.88 99.95 99.98 99.99 100.00 100.00 100.00 0.00

C 91.97 98.58 99.72 99.90 99.96 99.99 100.00 100.00 100.00 100.00 0.00

D 68.43 87.39 96.96 98.82 99.63 99.86 99.96 99.99 100.00 100.00 0.00

E 84.88 94.84 97.49 98.81 99.66 99.81 99.89 99.94 100.00 100.00 0.00

F 83.23 94.28 97.12 98.56 99.61 99.78 99.86 99.94 100.00 100.00 0.00

G 84.42 95.89 99.25 99.73 99.89 99.95 99.98 100.00 100.00 100.00 0.00

H 63.40 82.87 96.00 98.47 99.45 99.73 99.89 99.93 99.98 99.99 0.01

I 71.85 93.30 98.29 99.36 99.73 99.89 99.94 99.97 99.99 100.00 0.00

J 47.20 73.00 87.20 93.21 96.71 98.36 99.28 99.68 99.89 99.96 0.04

Right Thumb/Index Left Thumb/Index

Both Either None Both Either None

A 29.22 81.72 18.28 32.67 80.56 19.44

A+32 77.74 98.63 1.37 80.55 98.82 1.18

B 97.82 99.97 0.03 97.75 99.95 0.05

C 96.61 99.95 0.05 97.16 99.94 0.06

D 84.06 99.68 0.32 83.16 99.63 0.37

E 95.36 99.93 0.07 95.20 99.91 0.09

F 94.38 99.89 0.11 94.38 99.88 0.12

G 94.42 99.91 0.09 94.04 99.90 0.10

H 76.22 99.34 0.66 82.43 99.41 0.59

I 91.18 99.75 0.25 86.42 99.75 0.25

J 79.19 98.37 1.63 75.71 98.14 1.86

Right Thumb/Index/Middle Left Thumb/Index/Middle

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 20.47 63.16 90.53 9.47 24.75 64.00 90.79 9.21

A+32 71.59 95.04 99.35 0.65 74.87 95.65 99.43 0.57

B 97.19 99.86 99.99 0.01 97.14 99.82 99.98 0.02

C 96.27 99.88 99.99 0.01 96.73 99.88 99.98 0.02

D 83.15 98.66 99.89 0.11 81.99 98.92 99.91 0.09

E 94.08 98.50 99.95 0.05 93.46 98.31 99.96 0.04

F 92.96 98.26 99.93 0.07 92.38 98.14 99.94 0.06

G 93.47 99.67 99.96 0.04 92.67 99.66 99.97 0.03

H 75.09 98.47 99.80 0.20 80.92 98.54 99.82 0.18

I 90.16 99.29 99.91 0.09 85.21 99.27 99.89 0.11

J 76.13 96.39 99.50 0.50 72.74 94.36 99.35 0.65

Right Index/Middle/Ring Left Index/Middle/Ring

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 29.01 64.25 88.73 11.27 35.64 68.95 89.57 10.43

A+32 78.31 94.11 98.03 1.97 81.87 94.69 98.09 1.91

B 97.88 99.77 99.95 0.05 97.64 99.75 99.91 0.09

C 98.70 99.89 99.96 0.04 98.47 99.87 99.97 0.03

D 95.20 98.68 99.24 0.76 94.79 99.00 99.64 0.36

E 95.02 98.23 99.12 0.88 94.05 97.99 99.15 0.85

F 94.57 97.98 98.91 1.09 93.64 97.85 99.01 0.99

G 96.76 99.52 99.93 0.07 96.00 99.48 99.93 0.07

H 95.16 99.12 99.73 0.27 94.40 98.95 99.66 0.34

I 96.13 99.33 99.74 0.26 96.20 99.33 99.79 0.21

J 82.53 96.14 99.00 1.01 79.43 94.18 96.93 3.07
(C) Crease Ignored

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐5

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐5

Finger Position

RT RI RM RR RL LT LI LM LR LL

A 54.69 85.39 77.50 64.25 60.79 70.44 70.60 77.27 84.21 81.96

A+32 92.07 97.94 97.10 95.97 93.48 92.81 96.40 95.86 95.57 92.99

B 99.43 99.60 99.60 99.57 99.23 99.36 99.38 99.63 99.64 99.31

C 99.13 99.86 99.91 99.86 99.66 99.20 99.77 99.84 99.86 99.63

D 94.19 98.11 98.26 97.48 96.76 93.09 97.63 98.41 98.23 96.90

E 99.09 97.30 97.63 98.29 98.16 98.85 97.14 97.03 97.90 97.54

F 99.03 97.12 97.38 98.01 98.22 98.71 97.03 96.76 97.73 97.69

G 97.39 99.52 99.64 99.11 98.79 97.19 98.96 99.54 99.52 98.77

H 79.40 98.96 98.86 98.84 96.78 86.52 98.38 98.89 99.09 95.61

I 94.07 98.68 99.33 98.84 95.66 88.75 99.02 99.40 99.06 96.61

J 93.75 92.78 95.37 92.04 88.17 94.85 88.39 93.63 90.98 88.77

Thumb Index Middle Ring Little

Both Either None Both Either None Both Either None Both Either None Both Either None

A 43.85 81.28 18.72 60.64 95.36 4.64 60.48 94.28 5.72 54.82 93.64 6.36 50.90 91.84 8.16

A+32 89.26 95.62 4.38 94.59 99.75 0.25 93.33 99.64 0.36 91.98 99.57 0.43 87.82 98.65 1.35

B 98.94 99.86 0.14 99.02 99.97 0.03 99.25 99.99 0.01 99.24 99.98 0.02 98.57 99.97 0.03

C 98.54 99.79 0.21 99.63 0.00 0.00 99.75 0.00 0.00 99.73 99.99 0.01 99.30 99.99 0.01

D 90.34 96.94 3.06 95.84 99.90 0.10 96.80 99.86 0.14 95.91 99.80 0.20 93.94 99.72 0.28

E 98.16 99.78 0.22 94.72 99.71 0.29 94.96 99.70 0.30 96.41 99.77 0.23 95.95 99.75 0.25

F 98.05 99.69 0.31 94.51 99.64 0.36 94.45 99.68 0.32 95.98 99.76 0.24 96.15 99.77 0.23

G 96.17 98.41 1.59 98.49 99.99 0.01 99.19 99.99 0.01 98.65 99.97 0.03 97.60 99.96 0.04

H 77.00 88.92 11.08 97.43 99.91 0.09 97.85 99.89 0.11 98.03 99.91 0.09 92.80 99.59 0.41

I 84.26 98.56 1.44 97.79 99.91 0.09 98.77 99.96 0.04 97.97 99.93 0.07 92.78 99.48 0.52

J 90.27 98.33 1.67 83.21 97.96 2.04 89.81 99.19 0.81 84.99 98.03 1.97 79.90 97.03 2.97

Right Hand (w/Thumbs) Left Hand (w/Thumbs)

All 5 Any 4 Any 3 Any 2 Any 1 None All 5 Any 4 Any 3 Any 2 Any 1 None

A 18.57 52.88 79.29 93.24 98.63 1.37 34.87 69.09 86.40 95.03 99.09 0.91

A+32 82.34 96.40 98.64 99.28 99.89 0.11 81.37 95.43 98.06 98.90 99.87 0.13

B 97.79 99.80 99.88 99.97 100.00 0.00 97.75 99.76 99.87 99.95 100.00 0.00

C 98.54 99.93 99.98 99.99 100.00 0.00 98.48 99.89 99.95 99.98 100.00 0.00

D 88.21 98.04 99.08 99.50 99.96 0.04 86.80 98.22 99.42 99.84 99.98 0.02

E 93.90 98.08 98.98 99.52 99.99 0.01 92.42 97.66 98.88 99.50 100.00 0.00

F 93.73 97.86 98.79 99.41 99.98 0.02 92.24 97.52 98.77 99.39 99.99 0.01

G 94.93 99.64 99.91 99.97 100.00 0.00 94.47 99.61 99.92 99.97 100.00 0.00

H 75.40 98.08 99.61 99.79 99.96 0.04 81.08 98.29 99.49 99.69 99.94 0.06

I 88.39 98.74 99.68 99.84 99.94 0.06 84.62 98.77 99.64 99.84 99.96 0.04

J 72.94 92.55 97.64 99.08 99.90 0.10 72.27 91.28 95.93 97.31 99.84 0.16

Right Hand Left Hand

All 4 Any 3 Any 2 Any 1 None All 4 Any 3 Any 2 Any 1 None

A 33.67 67.99 88.75 97.24 2.76 48.25 77.74 90.82 97.11 2.89

A+32 88.73 97.35 98.90 99.39 0.61 86.97 96.29 98.27 98.99 1.01

B 98.29 99.81 99.88 99.97 0.03 98.32 99.76 99.87 99.95 0.05

C 99.34 99.95 99.98 99.99 0.01 99.20 99.91 99.94 99.97 0.03

D 93.52 98.36 99.13 99.50 0.50 93.07 98.59 99.47 99.86 0.14

E 94.65 98.09 98.96 99.52 0.48 93.22 97.72 98.90 99.49 0.51

F 94.51 97.88 98.78 99.41 0.59 93.17 97.58 98.80 99.38 0.62

G 97.37 99.72 99.93 99.98 0.02 97.10 99.67 99.92 99.99 0.01

H 94.51 99.26 99.70 99.83 0.17 93.28 99.18 99.60 99.72 0.28

I 93.72 99.18 99.72 99.86 0.14 95.05 99.31 99.70 99.89 0.11

J 77.08 93.56 97.92 99.25 0.75 75.45 92.18 96.13 97.42 2.58
(C) Crease Ignored

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐6

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

A‐6

Person

All 10 Any 9 Any 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 8.51 27.02 49.71 69.84 83.92 92.37 96.98 99.01 99.77 99.96 0.04

A+32 71.45 87.95 95.18 97.43 98.94 99.54 99.83 99.92 99.97 99.99 0.01

B 95.89 99.31 99.71 99.91 99.98 99.99 100.00 100.00 100.00 100.00 0.00

C 97.29 99.61 99.90 99.95 99.98 100.00 100.00 100.00 100.00 100.00 0.00

D 79.41 93.08 97.93 99.07 99.73 99.90 99.97 99.99 100.00 100.00 0.00

E 87.58 95.47 97.66 98.87 99.71 99.82 99.89 99.95 100.00 100.00 0.00

F 87.31 95.14 97.37 98.62 99.66 99.79 99.87 99.94 100.00 100.00 0.00

G 91.27 97.61 99.69 99.92 99.97 99.99 100.00 100.00 100.00 100.00 0.00

H 69.09 85.90 97.71 99.23 99.70 99.86 99.94 99.95 99.99 100.00 0.00

I 76.06 95.33 98.88 99.56 99.78 99.91 99.95 99.97 99.99 100.00 0.00

J 57.06 80.75 90.54 94.70 97.57 98.85 99.51 99.81 99.94 100.00 0.00

Right Thumb/Index Left Thumb/Index

Both Either None Both Either None

A 47.10 92.98 7.02 50.33 90.72 9.28

A+32 90.39 99.61 0.39 89.61 99.60 0.40

B 99.05 99.98 0.02 98.77 99.98 0.02

C 99.01 99.98 0.02 99.00 99.98 0.02

D 92.43 99.87 0.13 90.92 99.79 0.21

E 96.43 99.96 0.04 96.06 99.93 0.07

F 96.18 99.97 0.03 95.84 99.90 0.10

G 96.95 99.96 0.04 96.19 99.95 0.05

H 78.71 99.65 0.35 85.24 99.66 0.34

I 92.93 99.82 0.18 87.98 99.79 0.21

J 87.25 99.27 0.73 84.01 99.23 0.77

Right Thumb/Index/Middle Left Thumb/Index/Middle

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 37.90 82.55 97.13 2.87 42.17 79.85 96.29 3.71

A+32 88.70 98.59 99.82 0.18 87.13 98.13 99.81 0.19

B 98.72 99.92 100.00 0.00 98.51 99.89 99.99 0.01

C 98.95 99.96 100.00 0.00 98.87 99.95 99.99 0.01

D 91.65 98.96 99.95 0.05 89.93 99.26 99.94 0.06

E 95.48 98.57 99.97 0.03 94.65 98.39 99.98 0.02

F 95.21 98.34 99.98 0.02 94.29 98.25 99.95 0.05

G 96.69 99.87 99.99 0.01 95.82 99.88 99.99 0.01

H 78.14 99.20 99.89 0.11 84.65 99.24 99.91 0.09

I 92.64 99.52 99.93 0.07 87.69 99.57 99.91 0.09

J 84.33 97.78 99.78 0.22 81.50 95.64 99.73 0.27

Right Index/Middle/Ring Left Index/Middle/Ring

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 48.54 82.54 96.05 3.95 53.69 83.38 95.01 4.99

A+32 93.27 98.44 99.30 0.70 91.14 97.81 98.88 1.12

B 98.96 99.86 99.96 0.04 98.91 99.84 99.91 0.09

C 99.69 99.96 99.98 0.02 99.55 99.95 99.97 0.03

D 95.85 98.76 99.24 0.76 95.53 99.09 99.64 0.36

E 95.77 98.32 99.13 0.87 94.83 98.09 99.15 0.85

F 95.52 98.08 98.92 1.08 94.56 97.94 99.02 0.98

G 98.48 99.83 99.97 0.03 98.19 99.85 99.97 0.03

H 97.34 99.54 99.77 0.23 97.16 99.48 99.72 0.28

I 97.51 99.55 99.80 0.20 98.06 99.61 99.82 0.18

J 84.41 96.67 99.10 0.90 81.27 94.68 97.05 2.95
Appendix B. Result tables for 2-inch slap images. 

This appendix shows successful segmentation rates for the 2-inch slap images 

by finger position, hand, and various combinations of fingers that may be of 

interest to different fingerprint matching applications. 

The first table shows successful segmentation percentages for each finger 

position. 

The second table combines the right and left hand for each finger position and 

shows results for getting both the right and left finger, either or none. 

The third table looks at the results by right and left hand. Columns show 

segmentation rates for correctly segmenting all 5 finger positions, any 4, any 3, 

down to none. 

The fourth table is shows results for all ten fingers by combining right and left 

hands. 

The last two tables show results for finger position combinations of index/middle 

and index/middle/ring. 

All seven tables are then repeated (B) for the case where the maximum limited of 

the bottom (which is the bottom left and right y-positions) is ignored and then 

repeated (C) again ignoring the bottom (crease) completely. This was done as 

previous work had shown the crease is usually the most difficult edge for the 

segmentation algorithm to detect. The results in these tables show algorithm J 

definitely had difficulty detecting the crease and many other algorithms show 

significant increases in successfully segmenting “All 5” finger positions on a hand 

when the crease is ignored. Again, this is not a surprise as detecting the correct 

crease is a known difficulty for segmentation algorithms. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
L/R -32/+64, T -64/+64, B -64/+128, Angle -/+5o

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐1

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐1

J 39 23 77 89 22 11 26 83 64 91 35 09 35 48 72 65 27 35 51 39 88 57 11 43

Finger Position

RI RM RR RL LI LM LR LL

A 54.75 53.70 46.18 42.36 51.74 48.91 49.65 47.81

A+32 86.61 82.75 83.86 89.21 86.99 81.61 84.94 90.76

B 95.88 96.33 96.93 97.95 96.41 95.90 96.39 97.37

C 97.42 97.67 97.98 98.87 98.53 97.85 97.97 98.73

E 97.57 97.90 97.97 98.60 97.73 97.11 96.94 98.31

F 97.25 97.93 98.26 98.76 98.28 97.55 97.54 98.84

G 95.95 96.25 96.44 97.02 97.28 95.44 95.87 96.23

H 94.49 92.20 96.00 95.95 95.39 94.60 94.30 93.33

I 95.17 95.49 95.78 97.41 95.67 95.03 95.13 97.43

J 61.99 46.08 53.49 71.75 56.93 45.92 54.81 68.36

Index Middle Ring Little

Both Either None Both Either None Both Either None Both Either None

A 29.39 75.24 24.76 27.31 74.70 25.30 24.29 71.52 28.48 20.96 68.24 31.76

A+32 74.59 97.06 2.94 68.04 94.33 5.67 71.26 95.35 4.65 76.87 97.35 2.65

B 92.94 99.70 0.30 92.73 99.53 0.47 94.02 99.63 0.37 95.36 99.82 0.18

C 96.06 99.89 0.11 95.47 99.81 0.19 96.44 99.86 0.14 97.67 99.89 0.11

E 95.16 99.75 0.25 94.95 99.70 0.30 95.12 99.73 0.27 96.57 99.77 0.23

F 95.77 99.87 0.13 95.48 99.84 0.16 96.15 99.87 0.13 97.57 99.98 0.02

G 93.42 99.72 0.28 91.97 99.30 0.70 92.82 99.42 0.58 93.00 99.52 0.48

H 89.88 99.09 0.91 87.90 98.54 1.46 91.11 98.88 1.12 89.34 98.82 1.18

I 91.08 99.49 0.51 90.80 99.28 0.72 91.41 99.49 0.51 94.78 99.79 0.21

J 39.23 77.89 22.11 26.83 64.91 35.09 35.48 72.65 27.35 51.39 88.57 11.43

Right Hand Left Hand

All 4 Any 3 Any 2 Any 1 None All 4 Any 3 Any 2 Any 1 None

A 18.63 40.34 60.00 78.02 21.98 19.30 41.46 59.98 77.37 22.63

A+32 64.09 86.20 94.41 97.74 2.26 66.06 86.35 94.13 97.77 2.23

B 91.05 97.70 98.88 99.46 0.54 90.31 97.54 98.80 99.43 0.57

C 94.01 98.76 99.45 99.73 0.27 94.67 99.01 99.57 99.81 0.19

E 92.98 99.31 99.80 99.95 0.05 91.71 98.80 99.70 99.88 0.12

F 93.12 99.36 99.79 99.92 0.08 93.34 99.18 99.80 99.89 0.11

G 89.62 97.48 98.99 99.57 0.43 90.03 96.94 98.58 99.27 0.73

H 83.12 96.85 99.09 99.59 0.41 83.78 96.16 98.52 99.16 0.84

I 89.19 97.03 98.48 99.15 0.85 88.58 96.92 98.53 99.24 0.76

J 24.96 49.96 71.08 87.31 12.69 21.76 46.95 69.50 87.81 12.19
L/R -32/+64, T -64/+64, B -64/+128, Angle -/+5o

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐2

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐2

I 92 31 98 35 92 30 98 39

Person

All 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 4.86 13.54 25.01 39.39 57.06 73.05 84.81 93.94 6.06

A+32 43.79 68.15 81.47 89.33 95.18 97.93 99.25 99.76 0.24

B 83.43 94.89 97.35 98.53 99.67 99.91 99.96 99.98 0.02

C 89.57 97.36 98.82 99.47 99.92 99.98 99.98 99.99 0.01

E 85.12 96.81 99.15 99.74 99.94 100.00 100.00 100.00 0.00

F 87.30 97.97 99.48 99.80 99.98 100.00 100.00 100.00 0.00

G 81.56 93.47 96.85 98.31 99.44 99.73 99.88 99.94 0.06

H 70.97 90.67 96.15 97.93 98.98 99.46 99.62 99.77 0.23

I 79.50 92.98 96.39 98.00 99.58 99.84 99.90 99.94 0.06

J 8.60 22.37 37.59 52.58 68.04 80.35 91.07 96.37 3.63

Right Index/Middle Left Index/Middle

Both Either None Both Either None

A 38.35 70.10 29.90 33.94 66.72 33.28

A+32 75.11 94.25 5.75 75.33 93.27 6.73

B 93.60 98.60 1.40 93.67 98.63 1.37

C 95.72 99.37 0.63 96.85 99.52 0.48

E 95.69 99.77 0.23 95.26 99.58 0.42

F 95.44 99.74 0.26 96.13 99.70 0.30

G 93.12 99.09 0.91 94.00 98.71 1.29

H 88.06 98.63 1.37 91.49 98.51 1.49

I 92.31 98.35 1 6.5 92.30 98.39 1 6.1

J 36.86 71.21 28.79 35.86 66.99 33.01

Right Index/Middle/Ring Left Index/Middle/Ring

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 26.61 53.01 75.01 24.99 25.65 51.29 73.37 26.63

A+32 67.96 88.91 96.35 3.65 69.56 88.41 95.57 4.43

B 92.05 97.98 99.11 0.89 91.72 97.89 99.09 0.91

C 94.53 98.95 99.58 0.42 95.48 99.18 99.68 0.32

E 94.11 99.45 99.88 0.12 92.92 99.07 99.80 0.20

F 94.09 99.49 99.87 0.13 94.17 99.33 99.86 0.14

G 91.15 98.08 99.42 0.58 91.83 97.64 99.12 0.88

H 85.57 97.73 99.39 0.61 87.94 97.37 98.98 1.02

I 90.14 97.53 98.76 1.24 89.52 97.39 98.91 1.09

J 28.86 54.84 77.86 22.14 28.80 53.16 75.70 24.30
(B) Ignore Crease

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐3

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐3

J 67 27 93 84 57 16 90 00 10 00 67 29 92 68 71 19 94 01

Finger Position

RI RM RR RL LI LM LR LL

A 70.63 69.35 65.19 55.36 63.80 57.49 60.08 53.38

A+32 92.78 89.90 92.47 95.52 92.42 87.29 91.12 94.11

B 96.52 96.87 97.67 98.41 97.26 97.15 97.63 97.79

C 97.71 98.02 98.49 99.08 98.84 98.67 98.94 98.95

E 98.52 98.61 98.84 99.43 99.09 98.77 98.62 99.27

F 98.20 98.62 98.90 99.37 98.98 98.87 98.69 99.29

G 96.90 97.27 97.44 97.55 97.98 96.84 97.31 96.94

H 95.77 93.00 97.21 97.20 96.47 95.90 96.27 95.49

I 96.57 96.98 97.23 97.85 96.98 97.24 97.44 97.79

J 78.59 69.47 78.31 81.87 81.98 76.71 80.52 83.07

Index Middle Ring Little

Both Either None Both Either None Both Either None Both Either None

A 44.82 87.03 12.97 40.53 85.69 14.31 39.09 85.13 14.87 30.18 76.91 23.09

A+32 84.35 98.86 1.14 78.05 96.97 3.03 82.46 98.27 1.73 84.73 98.56 1.44

B 94.36 99.80 0.20 94.51 99.66 0.34 95.79 99.83 0.17 96.29 99.87 0.13

C 96.65 99.90 0.10 96.76 99.86 0.14 97.73 99.94 0.06 98.19 99.92 0.08

E 97.77 99.97 0.03 97.49 99.90 0.10 97.76 99.91 0.09 98.79 99.99 0.01

F 97.31 99.97 0.03 97.61 99.95 0.05 97.94 99.94 0.06 98.73 99.99 0.01

G 94.86 99.80 0.20 94.27 99.56 0.44 95.04 99.64 0.36 94.20 99.61 0.39

H 92.25 99.30 0.70 89.73 98.86 1.14 94.17 99.19 0.81 92.60 99.19 0.81

I 93.65 99.72 0.28 94.60 99.74 0.26 95.03 99.78 0.22 95.73 99.85 0.15

J 67.27 93.84 6 1.6 57.16 90.00 10.00 67.29 92.68 7 3.2 71.19 94.01 5 9.9

Right Hand Left Hand

All 4 Any 3 Any 2 Any 1 None All 4 Any 3 Any 2 Any 1 None

A 35.86 59.96 76.16 88.54 11.46 28.15 51.64 69.31 85.66 14.34

A+32 80.71 93.44 97.49 99.02 0.98 78.14 91.73 96.45 98.62 1.38

B 93.14 97.93 98.94 99.47 0.53 93.56 97.96 98.88 99.43 0.57

C 95.22 98.88 99.47 99.73 0.27 96.67 99.29 99.62 99.82 0.18

E 96.04 99.58 99.82 99.95 0.05 96.47 99.57 99.82 99.90 0.10

F 95.78 99.57 99.81 99.92 0.08 96.55 99.55 99.84 99.90 0.10

G 92.48 98.00 99.10 99.58 0.42 93.32 97.66 98.77 99.32 0.68

H 86.68 97.63 99.24 99.63 0.37 88.91 97.22 98.76 99.24 0.76

I 93.18 97.62 98.64 99.20 0.80 93.58 97.84 98.75 99.29 0.71

J 56.44 76.14 84.77 90.90 9.10 64.24 79.60 86.79 91.65 8.35
(B) Ignore Crease

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐4

A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

B‐4

I 94 95 98 60 95 47 98 75

Person

All 8 Any 7 Any 6 Any 5 Any 4 Any 3 Any 2 Any 1 None

A 11.38 25.78 41.47 58.12 74.98 86.43 93.49 97.73 2.27

A+32 61.66 80.57 89.35 94.22 97.77 99.09 99.67 99.92 0.08

B 88.38 95.77 97.64 98.66 99.77 99.94 99.98 99.98 0.02

C 92.60 97.93 98.99 99.53 99.93 99.98 99.98 100.00 0.00

E 93.12 98.99 99.62 99.88 99.98 100.00 100.00 100.00 0.00

F 92.93 98.99 99.69 99.86 99.98 100.00 100.00 100.00 0.00

G 86.77 95.03 97.41 98.58 99.59 99.77 99.90 99.94 0.06

H 78.31 93.33 97.13 98.38 99.14 99.54 99.68 99.78 0.22

I 87.66 95.30 97.27 98.33 99.79 99.88 99.92 99.94 0.06

J 41.98 61.33 72.27 80.23 89.66 93.76 96.37 97.84 2.16

Right Index/Middle Left Index/Middle

Both Either None Both Either None

A 57.08 82.89 17.11 43.93 77.36 22.64

A+32 85.55 97.13 2.87 83.74 95.98 4.02

B 94.73 98.66 1.34 95.62 98.79 1.21

C 96.34 99.39 0.61 97.92 99.59 0.41

E 97.28 99.85 0.15 98.06 99.80 0.20

F 97.01 99.81 0.19 98.07 99.79 0.21

G 94.92 99.25 0.75 95.88 98.94 1.06

H 89.93 98.84 1.16 93.63 98.73 1.27

I 94.95 98.60 1 4.0 95.47 98.75 1 2.5

J 62.89 85.17 14.83 71.58 87.11 12.89

Right Index/Middle/Ring Left Index/Middle/Ring

All 3 Any 2 Any 1 None All 3 Any 2 Any 1 None

A 47.22 71.25 86.70 13.30 35.68 62.46 83.24 16.76

A+32 82.26 94.53 98.36 1.64 80.45 92.96 97.43 2.57

B 93.78 98.14 99.14 0.86 94.66 98.23 99.15 0.85

C 95.59 99.03 99.60 0.40 97.32 99.40 99.73 0.27

E 96.43 99.65 99.89 0.11 96.96 99.64 99.88 0.12

F 96.20 99.65 99.88 0.12 97.03 99.63 99.89 0.11

G 93.64 98.49 99.49 0.51 94.69 98.24 99.21 0.79

H 88.28 98.23 99.46 0.54 91.47 98.03 99.13 0.87

I 93.90 98.01 98.88 1.13 94.36 98.25 99.05 0.95

J 58.91 79.03 88.44 11.56 67.31 82.40 89.50 10.50
Appendix C. Detailed segmentation statistics. 

The tables is this appendix show distribution statistics, by finger position, for the 

segmentation algorithms tested as compared to the hand marked ground truth for 

3-inch slap images. The differences between the segmentation algorithm and 

ground truth are sorted into bins based on the tolerances allowed for correct 

segmentation. Specifically, the left/right edges must be within -32/+64 pixels of 

the ground truth, top edge -64/+64 and bottom edge -64/+128. For each finger 

position there is a column for each of the four segmentation box edges (L, R, T 

and B). 

The first row (“No Finger Found”) shows the counts for when a finger was not 

detected by the segmentation algorithm. The next four rows show statistics for 

segmentation edges that are within the specified minimum (MN) and maximum 

(MX) pixel tolerances compared to the ground truth, so these are considered 

good segmentations. Rows 1 (MN <= d < 0) and 3 (0 <= d <= MX) show the 

average value for all differences in that range and rows 3 and 5 show the total 

count occurring in that range. 

Rows 6-9 also show average difference values and bin counts but for ranges 

MN-32 <= d < MN and MX < d <= MX+32, which are just outside the accepted 

tolerance ranges. Rows 10-13 tally everything greater than 32 pixels away from 

the accepted tolerance range, d < MN-32 and d > MX+32. 

The last three rows show the total count for each bin, the overall average 

difference value and the standard deviation of all the difference values. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
ex

ex 

A

R. Thumb R. Ind R Middle R. Ring

No Finger Found 89 121 76 101

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐11.51 ‐22.67 ‐18.73 ‐39.86 ‐13.91 ‐19.45 ‐24.28 ‐44.11 ‐13.44 ‐21.10 ‐24.59 ‐42.53 ‐10.87 ‐22.12 ‐24.91 ‐43.57 

# 17025 13116 21205 13835 21015 21047 23131 19172 19954 18639 22768 17533 18472 15578 22580 16069 

0 <= d <= MX 6.89 17.68 7.81 44.54 8.18 8.81 9.97 37.99 8.91 11.52 10.55 45.39 7.67 13.60 11.92 42.42 

# 5859 543 1942 1821 3195 686 1501 636 4234 1069 1836 1761 6012 657 1912 1463 

MN‐32 <= d < MN ‐38.17 ‐40.47 ‐77.62 ‐76.81 ‐37.47 ‐37.47 ‐73.54 ‐73.72 ‐36.90 ‐38.41 ‐77.98 ‐74.94 ‐38.79 ‐39.80 ‐74.05 ‐75.30 

# 333 9284 113 4530 532 2998 25 3766 518 4945 25 3022 150 8224 38 4017 

MX < d <= MX+32 80.98 80.79 77.80 143.34 78.66 78.00 77.63 142.43 74.74 78.45 76.89 143.89 74.84 78.19 78.82 140.11 

# 32 54 23 131 29 8 19 43 25 19 46 97 19 24 53 57 

d < MN‐32 ‐322.82 ‐375.06 ‐244.13 ‐316.03 ‐246.71 ‐334.77 ‐730.13 ‐229.76 ‐253.14 ‐375.12 ‐596.86 ‐166.86 ‐199.63 ‐385.92 ‐764.44 ‐166.12 

# 623 998 162 3897 21 209 130 876 33 271 215 2018 43 456 134 2934 

d > MX+32 498.17 228.12 656.17 228.17 232.55 313.20 354.11 381.85 373.69 336.04 191.88 381.68 500.08 317.00 226.24 417.18 

# 550 427 977 208 176 20 162 475 204 25 78 537 272 29 251 428 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average ‐3.80 ‐38.33 8.71 ‐81.22 ‐9.94 ‐23.18 ‐23.41 ‐44.57 ‐7.20 ‐26.54 ‐26.13 ‐40.45 ‐1.27 ‐33.15 ‐23.38 ‐49.72 

Std Dev 101.52 107.18 142.20 173.12 25.87 36.93 64.65 89.41 40.47 49.76 67.46 90.71 62.67 75.05 66.67 93.59 

L. Thumb L. Ind L. Middle L. Ring

No Finger Found 35 210 125 180

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐13.81 ‐21.15 ‐20.82 ‐37.44 ‐10.87 ‐21.17 ‐23.92 ‐44.39 ‐12.62 ‐20.08 ‐23.62 ‐41.19 ‐14.29 ‐18.56 ‐23.34 ‐42.94 

# 18516 17439 21738 14492 18579 17324 23127 18849 18931 18557 22626 17823 19576 20539 22553 17431 

0 <= d <= MX 10.01 12.63 8.68 46.43 7.42 13.14 9.97 44.71 9.67 10.83 10.65 45.67 10.08 9.24 10.45 50.26 

# 3843 379 1482 2769 5897 497 1368 578 5340 1043 1849 2321 4294 1014 1812 2039 

MN‐32 <= d < MN ‐39.15 ‐38.27 ‐77.90 ‐76.62 ‐37.75 ‐39.93 ‐76.25 ‐73.72 ‐36.24 ‐39.48 ‐74.52 ‐74.38 ‐36.91 ‐38.76 ‐79.65 ‐74.56 

# 822 5377 102 3914 141 6592 28 3888 297 4885 42 2509 573 2848 26 3082 

MX < d <= MX+32 78.47 78.78 78.40 141.88 74.42 80.25 77.13 143.39 76.73 77.90 78.89 143.29 77.17 82.33 80.17 143.77 

# 73 29 25 168 18 28 12 54 41 15 35 133 62 3 53 93 

d < MN‐32 ‐414.71 ‐342.05 ‐308.29 ‐362.26 ‐277.95 ‐659.29 ‐665.22 ‐283.60 ‐303.80 ‐509.01 ‐546.62 ‐185.65 ‐302.54 ‐438.95 ‐659.31 ‐211.22 

# 634 718 135 2848 74 452 151 973 183 288 299 1514 224 334 177 1669 

d > MX+32 240.43 471.85 630.53 285.71 924.08 314.15 358.18 357.72 633.35 305.10 208.81 398.44 417.20 293.07 241.25 375.72 

# 534 480 940 231 255 71 278 622 172 176 113 664 235 226 343 650 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average ‐15.49 ‐24.02 4.32 ‐67.80 2.12 ‐35.93 ‐21.70 ‐45.79 ‐5.67 ‐25.87 ‐26.23 ‐32.53 ‐8.92 ‐22.52 ‐21.60 ‐38.89 

Std Dev 87.47 101.21 137.39 169.03 102.33 121.09 70.77 103.68 64.66 78.35 73.88 102.18 54.69 69.34 70.02 104.89 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐1
x L. 

x R

d <

B

R. Thumb R. Inde Middle R. Ring

No Finger Found 3 3 22 7

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐6.58 ‐7.54 ‐5.27 ‐17.34 ‐5.52 ‐6.42 ‐6.58 ‐12.57 ‐5.19 ‐6.36 ‐6.30 ‐18.40 ‐5.18 ‐7.80 ‐6.52 ‐19.45 

# 73 300 3983 5260 1448 1280 12371 1102 1375 1595 11723 1534 629 2732 11201 1827 

0 <= d <= MX 30.30 24.49 12.82 38.66 15.05 16.57 8.34 39.07 16.22 16.30 9.40 45.03 18.11 14.76 9.13 45.90 

# 24273 24042 20384 18769 23489 23609 12557 23739 23554 23280 13211 23198 24292 22146 13722 22785 

MN‐32 <= d < MN ‐55.00 ‐42.91 ‐81.36 ‐76.79 ‐40.14 ‐38.17 ‐80.83 ‐77.56 ‐34.00 ‐38.22 ‐91.00 ‐77.35 ‐37.00 ‐36.70 ‐85.83 ‐76.72 

# 3 11 11 205 7 6 6 16 1 9 3 67 1 46 6 145 

MX < d <= MX+32 70.09 77.09 76.25 139.80 #DIV/0! 71.27 78.50 138.84 75.25 71.02 80.50 137.46 76.50 80.20 88.50 139.60 

# 32 29 4 60 0 48 6 60 4 48 9 98 8 5 2 122 

d < MN‐32 ‐382.40 ‐839.57 ‐504.04 ‐204.12 ‐255.37 ‐216.25 ‐680.78 ‐196.92 ‐334.00 ‐811.44 ‐504.14 ‐383.98 ‐430.57 ‐662.00 ‐465.71 ‐167.78 

# 26 15 34 81 19 2 18 24 15 18 7 41 14 20 17 51 

d > MX+32 468.43 661.46 893.92 601.22 137.20 374.24 297.60 710.61 515.95 396.33 298.73 311.17 446.13 368.47 192.80 367.53 

# 15 25 6 47 5 23 10 27 19 18 15 30 24 19 20 38 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 30.06 24.25 9.34 26.15 13.66 15.79 0.56 37.45 15.22 14.61 2.07 40.78 17.70 11.94 1.91 40.92 

Std Dev 23.01 39.69 29.10 53.06 12.47 16.60 24.75 38.37 19.57 27.49 17.14 39.39 20.79 32.49 18.77 38.77 

L. Thumb L. Inde Middle L. Ring

No Finger Found 26 0 9 14

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐8.12 ‐5.40 ‐5.09 ‐16.44 ‐4.97 ‐8.57 ‐6.67 ‐12.66 ‐4.78 ‐7.12 ‐6.56 ‐18.11 ‐4.87 ‐7.25 ‐6.32 ‐19.02 

# 171 129 5548 5718 1165 2424 12213 1124 1494 1831 11640 1685 1908 1176 10772 2458 

0 <= d <= MX 27.60 26.08 11.76 37.55 16.41 15.28 8.34 40.22 16.23 16.83 9.50 45.50 15.16 18.39 10.24 42.80 

# 24121 24226 18818 18335 23721 22439 12708 23726 23410 23069 13285 23048 23006 23709 14141 22203 

MN‐32 <= d < MN ‐48.67 ‐46.13 ‐69.25 ‐77.79 ‐49.50 ‐37.15 ‐79.94 ‐77.09 ‐36.75 ‐36.25 ‐74.14 ‐77.53 ‐43.00 ‐40.07 ‐74.00 ‐76.67 

# 12 8 4 147 2 65 8 35 4 16 7 83 2 14 3 158 

MX < d <= MX+32 73.71 74.75 #DIV/0! 143.34 72.41 66.00 81.50 140.82 73.75 70.30 78.00 141.13 72.20 69.56 72.75 138.83 

# 77 4 0 65 44 2 2 28 16 10 5 63 5 25 4 48 

d < MN‐32 ‐444.04 ‐410.14 ‐391.29 ‐410.10 ‐890.50 ‐270.05 ‐550.20 ‐196.09 ‐665.50 ‐507.33 ‐340.93 ‐249.59 ‐416.58 ‐586.86 ‐536.54 ‐264.03 

# 13 43 26 96 13 20 15 23 7 30 22 29 13 29 23 64 

d > MX+32 306.38 650.79 842.35 312.57 312.05 1080.54 238.33 574.41 428.82 924.81 204.60 381.76 386.37 620.77 301.19 484.80 

# 28 12 26 61 19 14 18 28 33 8 5 56 30 11 21 33 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average 27.53 25.44 8.37 23.43 15.26 13.20 0.81 38.17 15.36 14.72 1.73 41.45 13.86 16.77 2.84 35.94 

Std Dev 19.75 29.46 34.67 57.72 26.00 31.14 20.21 34.89 23.16 29.40 17.22 39.52 20.73 29.88 24.73 44.42 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐2
x R

x L. 

d <

C

R. Thumb R. Inde Middle R. Ring

No Finger Found 5 3 5 7

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐6.29 ‐8.12 ‐9.53 ‐19.31 ‐6.30 ‐6.26 ‐8.07 ‐12.10 ‐5.05 ‐6.49 ‐8.18 ‐15.80 ‐4.56 ‐8.27 ‐7.41 ‐15.63 

# 1555 2809 7521 12352 866 568 13852 1543 662 655 14584 2069 303 1409 13778 1834 

0 <= d <= MX 21.08 17.86 12.50 26.05 13.91 17.65 10.33 31.92 15.31 17.10 11.50 35.85 18.23 16.51 11.40 36.02 

# 22825 21453 16825 11414 24081 24378 11096 23340 24294 24298 10372 22733 24647 23533 11176 22876 

MN‐32 <= d < MN ‐55.00 ‐42.12 ‐78.34 ‐76.48 ‐44.00 ‐41.43 ‐68.00 ‐73.00 ‐36.00 ‐43.33 ‐74.33 ‐76.04 ‐35.50 ‐39.00 ‐77.80 ‐77.84 

# 5 86 29 460 8 7 1 20 1 3 3 67 2 11 5 123 

MX < d <= MX+32 78.75 74.33 66.00 142.04 70.50 77.33 77.25 139.77 74.25 76.25 #DIV/0! 139.81 77.20 77.00 78.00 140.88 

# 4 21 1 23 2 3 4 32 4 4 0 52 5 4 2 73 

d < MN‐32 ‐373.85 ‐426.61 ‐421.94 ‐177.86 ‐285.44 ‐225.50 ‐584.40 ‐131.00 ‐437.00 ‐806.50 ‐280.50 ‐188.92 ‐590.40 ‐761.00 ‐411.50 ‐137.83 

# 26 31 40 140 9 1 15 8 6 1 7 19 5 3 6 41 

d > MX+32 600.29 689.64 1063.50 706.88 160.00 473.50 #DIV/0! 634.82 555.50 508.43 333.75 270.29 429.17 518.00 358.50 306.24 

# 7 22 6 33 2 11 0 25 1 7 2 28 6 8 1 21 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 19.08 14.75 5.16 1.04 13.10 17.29 ‐0.23 29.80 14.69 16.59 ‐0.06 31.58 17.94 15.17 0.92 31.92 

Std Dev 22.51 39.78 30.96 52.46 10.38 13.88 20.99 32.45 11.93 13.80 13.94 28.75 14.38 17.77 14.12 29.73 

L. Thumb L. Inde Middle L. Ring

No Finger Found 23 0 0 7

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐7.18 ‐5.71 ‐8.83 ‐19.02 ‐4.70 ‐8.88 ‐8.04 ‐11.92 ‐4.06 ‐6.91 ‐8.43 ‐16.12 ‐4.33 ‐7.64 ‐7.14 ‐15.86 

# 3399 562 8569 12199 435 1484 13617 1565 591 858 14364 2321 724 608 13279 2565 

0 <= d <= MX 16.97 22.09 12.35 25.74 16.17 17.25 10.33 31.64 15.52 18.60 11.33 35.15 15.37 19.87 12.57 32.68 

# 20873 23798 15781 11695 24504 23440 11329 23330 24347 24080 10577 22454 24218 24327 11663 22148 

MN‐32 <= d < MN ‐43.96 ‐44.31 ‐75.56 ‐77.19 ‐37.00 ‐36.46 ‐82.88 ‐75.96 ‐39.33 ‐40.25 ‐76.00 ‐76.63 #DIV/0! ‐42.71 ‐70.00 ‐78.65 

# 67 16 27 332 1 28 8 25 3 4 8 64 0 7 2 136 

MX < d <= MX+32 74.79 82.00 67.00 141.84 71.50 #DIV/0! #DIV/0! 140.86 77.14 70.17 80.50 139.02 69.13 74.40 76.00 139.73 

# 39 3 1 31 10 0 0 14 7 6 2 64 8 5 1 51 

d < MN‐32 ‐268.90 ‐448.90 ‐384.94 ‐309.73 ‐961.04 #DIV/0! ‐430.20 ‐125.29 ‐605.22 ‐395.50 ‐585.35 ‐113.70 ‐415.00 ‐701.22 ‐522.08 ‐197.12 

# 24 34 24 132 12 0 10 7 9 6 13 20 5 9 12 42 

d > MX+32 338.03 804.06 929.33 414.48 115.00 1234.79 #DIV/0! 517.24 385.29 848.80 #DIV/0! 431.52 602.11 496.94 365.29 502.73 

# 20 9 20 33 2 12 0 23 7 10 0 41 9 8 7 22 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average 13.52 21.05 5.19 0.84 15.36 16.22 0.10 29.26 14.95 17.95 ‐0.37 30.90 14.95 19.08 1.93 27.33 

Std Dev 21.08 28.64 34.20 55.21 23.95 29.53 16.18 27.63 16.43 20.57 19.37 34.52 15.99 19.69 19.20 34.87 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐3
x R

x L. 

d <

D

R. Thumb R. Inde Middle R. Ring

No Finger Found 54 225 18 10

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐10.86 ‐11.01 ‐12.47 ‐22.89 ‐9.54 ‐6.10 ‐15.37 ‐7.97 ‐10.55 ‐6.94 ‐16.12 ‐8.73 ‐7.90 ‐8.26 ‐15.81 ‐8.85 

# 19487 17757 17661 10815 20731 11835 20445 7373 20924 15032 20228 7437 19328 15741 20167 6366 

0 <= d <= MX 5.09 8.08 5.94 18.42 5.10 5.79 7.15 15.34 5.24 5.33 7.06 19.21 4.50 6.23 7.01 20.22 

# 4234 5984 6015 10793 3879 12834 4214 16830 3744 9608 4514 16476 5401 8766 4516 17516 

MN‐32 <= d < MN ‐38.94 ‐41.34 ‐78.32 ‐77.24 ‐39.24 ‐40.26 ‐76.63 ‐78.70 ‐36.83 ‐38.72 ‐76.88 ‐76.55 ‐37.96 ‐39.35 ‐73.80 ‐77.35 

# 225 475 120 1482 84 34 15 20 62 60 20 63 25 265 20 86 

MX < d <= MX+32 76.19 76.29 72.90 142.52 81.36 80.00 80.48 143.64 79.91 83.31 76.41 142.57 80.17 80.25 78.58 143.01 

# 26 33 5 112 28 13 25 277 16 26 11 477 12 22 57 516 

d < MN‐32 ‐197.91 ‐413.62 ‐349.33 ‐204.39 ‐214.11 ‐541.14 ‐632.00 ‐798.28 ‐330.43 ‐334.91 ‐248.22 ‐337.10 ‐453.23 ‐340.72 ‐329.17 ‐182.13 

# 399 122 551 1037 9 226 20 239 14 192 185 35 15 147 35 154 

d > MX+32 527.32 314.16 714.88 260.27 273.40 243.96 389.23 236.25 299.45 227.40 200.30 220.46 298.41 391.07 173.09 209.92 

# 51 51 70 183 237 26 249 229 208 50 10 480 187 27 173 330 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average ‐10.19 ‐8.13 ‐13.76 ‐12.75 ‐4.65 ‐4.57 ‐7.97 4.05 ‐5.79 ‐4.25 ‐13.57 16.37 ‐3.18 ‐4.95 ‐10.65 16.27 

Std Dev 39.38 47.47 71.37 81.85 29.81 53.68 48.42 89.98 31.45 35.65 26.89 46.99 32.29 36.70 24.70 44.67 

L. Thumb L. Inde Middle L. Ring

No Finger Found 35 106 19 43

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐12.54 ‐9.53 ‐13.94 ‐22.51 ‐9.53 ‐7.74 ‐15.59 ‐8.65 ‐10.71 ‐7.41 ‐16.10 ‐9.99 ‐11.08 ‐6.53 ‐15.82 ‐9.64 

# 19570 16968 19165 11764 19697 11707 20004 7106 20337 12767 19814 7497 20102 9317 18620 7945 

0 <= d <= MX 8.64 5.80 7.25 18.78 4.44 6.12 6.15 14.66 4.38 5.66 5.68 18.97 5.75 6.29 6.31 18.63 

# 3589 6505 4697 10033 5075 12768 4743 17286 4418 11903 4998 16472 4666 15400 6099 16021 

MN‐32 <= d < MN ‐40.70 ‐39.80 ‐77.82 ‐77.10 ‐40.56 ‐40.07 ‐75.65 ‐75.82 ‐39.36 ‐38.13 ‐76.00 ‐76.53 ‐38.73 ‐38.34 ‐78.63 ‐78.28 

# 540 165 104 1441 32 315 17 19 36 125 25 70 66 88 8 91 

MX < d <= MX+32 75.61 77.90 78.22 142.58 79.33 78.87 78.88 142.40 79.32 79.70 73.83 142.29 80.90 82.74 77.46 142.56 

# 33 30 43 128 12 30 29 206 22 23 15 466 20 21 45 488 

d < MN‐32 ‐548.76 ‐276.42 ‐318.98 ‐190.05 ‐523.58 ‐1164.50 ‐399.56 ‐713.25 ‐318.44 ‐577.07 ‐288.91 ‐320.52 ‐322.53 ‐590.30 ‐369.87 ‐337.25 

# 651 171 337 920 13 116 39 128 81 46 94 54 30 64 41 125 

d > MX+32 461.78 597.55 511.84 259.98 826.33 367.57 374.32 242.15 366.52 324.62 209.64 219.56 378.18 279.49 206.07 216.29 

# 39 583 76 136 135 28 132 219 70 100 18 405 80 74 151 294 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average ‐23.47 7.08 ‐12.55 ‐12.64 ‐2.43 ‐5.91 ‐9.93 7.27 ‐7.94 ‐0.97 ‐12.61 14.83 ‐7.06 0.69 ‐9.50 12.25 

Std Dev 98.14 103.26 56.14 71.67 69.97 86.41 37.54 65.68 32.51 40.01 23.94 48.05 28.27 38.11 28.34 52.49 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐4
x R

x L. 

d <

E

R. Thumb R. Inde Middle R. Ring

No Finger Found 15 63 30 21

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐4.31 ‐5.44 ‐10.48 ‐12.86 ‐4.55 ‐6.16 ‐10.12 ‐11.19 ‐2.68 ‐6.59 ‐10.35 ‐12.65 ‐3.15 ‐7.74 ‐10.54 ‐11.75 

# 508 450 15905 6242 780 185 16537 691 819 222 15757 1157 356 658 15161 891 

0 <= d <= MX 18.97 20.31 5.62 22.99 22.98 28.02 10.88 35.88 23.27 26.02 11.55 35.31 23.76 24.47 11.68 36.91 

# 23883 23803 8441 17021 23813 24257 8296 23602 23702 24338 9130 22881 24371 23942 9728 23067 

MN‐32 <= d < MN ‐45.00 ‐43.50 ‐78.42 ‐77.31 ‐44.88 ‐40.90 ‐74.94 ‐74.63 ‐49.00 ‐35.50 ‐74.80 ‐78.80 ‐48.50 ‐37.50 ‐67.00 ‐76.75 

# 2 13 33 149 4 5 9 16 2 2 5 79 3 1 6 64 

MX < d <= MX+32 69.83 74.25 #DIV/0! 143.76 73.70 75.24 68.33 144.71 74.30 75.72 75.17 143.30 76.04 75.82 85.00 144.32 

# 3 110 0 349 274 399 3 160 347 281 9 268 156 262 3 368 

d < MN‐32 ‐435.97 ‐640.64 ‐291.91 ‐220.50 ‐302.92 ‐437.45 ‐771.69 ‐729.27 ‐444.00 ‐533.21 ‐506.05 ‐350.57 ‐195.18 ‐540.65 ‐784.56 ‐257.37 

# 17 14 34 108 6 57 61 62 4 49 46 45 11 47 25 63 

d > MX+32 589.17 390.59 788.17 219.11 176.73 160.23 373.44 285.56 296.27 142.57 186.45 235.08 417.15 153.87 221.18 223.98 

# 9 32 9 553 91 65 62 437 94 76 21 538 71 58 45 515 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 18.38 20.15 ‐5.10 18.30 23.15 27.79 ‐4.07 37.68 24.08 25.54 ‐3.07 37.49 24.72 23.40 ‐2.24 39.58 

Std Dev 20.25 30.18 23.96 55.57 18.36 28.39 45.65 62.89 26.05 31.96 29.60 48.24 29.45 34.36 30.76 46.44 

L. Thumb L. Inde Middle L. Ring

No Finger Found 12 58 18 21

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐2.68 ‐6.59 ‐10.35 ‐12.65 ‐2.90 ‐8.46 ‐10.18 ‐9.90 ‐2.26 ‐7.06 ‐10.50 ‐12.84 ‐2.49 ‐8.27 ‐10.39 ‐10.55 

# 819 222 15757 1157 568 648 16181 658 852 335 15211 1272 1022 235 14177 1241 

0 <= d <= MX 23.27 26.02 11.55 35.31 23.66 27.73 11.41 35.57 22.63 28.57 11.63 34.00 22.06 29.10 12.34 33.94 

# 23702 24338 9130 22881 23947 23825 8654 23586 23793 23968 9689 22675 23579 24373 10712 22663 

MN‐32 <= d < MN ‐49.00 ‐35.50 ‐74.80 ‐78.80 ‐33.50 ‐36.36 ‐75.15 ‐81.36 ‐33.50 ‐42.83 ‐70.50 ‐76.76 #DIV/0! ‐50.00 ‐80.83 ‐76.44 

# 2 2 5 79 1 7 10 21 1 3 6 80 0 8 3 50 

MX < d <= MX+32 74.30 75.72 75.17 143.30 74.98 74.33 73.67 143.00 75.67 74.78 73.94 144.03 74.85 73.59 82.67 144.28 

# 347 281 9 268 339 382 6 162 234 540 9 311 272 270 3 408 

d < MN‐32 ‐444.00 ‐533.21 ‐506.05 ‐350.57 ‐481.10 ‐1280.12 ‐698.51 ‐701.03 ‐338.55 ‐795.10 ‐617.13 ‐295.81 ‐281.98 ‐547.52 ‐737.25 ‐271.04 

# 4 49 46 45 5 53 57 55 21 20 39 36 22 22 36 70 

d > MX+32 296.27 142.57 186.45 235.08 606.40 171.80 352.35 267.87 285.77 193.97 232.10 233.10 213.26 246.42 293.71 232.46 

# 94 76 21 538 104 49 56 482 63 98 10 590 69 56 33 532 

Total # 24968 24968 24968 24968 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average 24.08 25.54 ‐3.07 37.49 26.07 24.99 ‐3.46 37.84 22.64 29.07 ‐2.74 36.86 21.89 29.19 ‐1.28 36.69 

Std Dev 26.05 31.96 29.60 48.24 52.47 64.86 40.41 57.95 26.72 34.21 31.29 49.18 21.25 26.26 34.78 50.79 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐5
x R

x L 

d <

F

R. Thumb R. Inde Middle R. Ring

No Finger Found 9 102 58 41

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐4.32 ‐5.55 ‐9.82 ‐15.60 ‐4.57 ‐6.29 ‐9.73 ‐10.64 ‐2.81 ‐6.30 ‐9.95 ‐11.92 ‐3.40 ‐7.35 ‐10.08 ‐11.92 

# 367 263 13876 7318 770 192 15863 1124 797 221 15174 1949 282 719 14590 1543 

0 <= d <= MX 20.67 22.66 7.57 23.63 23.04 28.28 11.20 31.31 23.41 26.21 11.81 29.54 23.96 24.53 11.97 31.60 

# 24010 23949 10488 16163 23777 24196 8937 23392 23655 24297 9686 22595 24390 23843 10270 22930 

MN‐32 <= d < MN ‐53.50 ‐49.00 ‐78.04 ‐77.25 ‐41.00 ‐44.17 ‐79.50 ‐74.62 #DIV/0! ‐36.50 ‐71.70 ‐76.42 ‐51.50 ‐41.00 ‐70.83 ‐77.27 

# 1 6 14 290 2 3 11 26 0 2 5 94 5 2 6 87 

MX < d <= MX+32 72.64 73.58 75.75 143.56 74.70 75.84 74.64 142.71 74.85 75.05 74.23 140.83 74.18 76.16 75.72 143.59 

# 14 154 6 181 291 417 7 145 371 286 15 108 182 277 9 186 

d < MN‐32 ‐692.11 ‐619.17 ‐377.64 ‐188.03 ‐255.63 ‐442.55 ‐723.63 ‐730.89 ‐360.50 ‐587.45 ‐364.11 ‐394.74 ‐261.08 ‐680.40 ‐591.28 ‐393.34 

# 19 12 25 148 4 96 49 101 3 85 44 84 6 72 25 79 

d > MX+32 435.68 514.20 592.65 235.70 191.60 142.38 358.45 350.90 331.27 129.29 194.66 266.05 482.54 148.55 245.63 265.53 

# 11 38 13 322 124 64 101 180 142 77 44 138 103 55 68 143 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 19.96 23.11 ‐2.42 13.08 23.58 27.29 ‐2.16 29.18 25.04 24.71 ‐1.73 26.27 25.83 22.42 ‐0.88 29.37 

Std Dev 25.99 35.03 24.98 52.26 19.82 33.85 43.09 65.26 31.56 41.64 24.75 43.17 38.05 47.35 28.69 45.25 

L. Thumb L. Inde . Middle L. Ring

No Finger Found 5 89 40 47

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐5.22 ‐3.99 ‐11.03 ‐15.99 ‐2.83 ‐8.63 ‐9.85 ‐9.90 ‐2.27 ‐7.26 ‐10.13 ‐11.96 ‐2.64 ‐7.61 ‐10.04 ‐11.26 

# 380 167 15726 7299 509 666 15589 1183 797 339 14662 2285 989 237 13781 2272 

0 <= d <= MX 21.16 22.96 7.39 23.65 23.74 27.70 11.54 30.40 22.54 28.67 11.72 28.14 21.81 29.32 12.59 28.06 

# 23757 24202 8637 16133 23984 23752 9224 23337 23814 23894 10212 22238 23588 24324 11080 22188 

MN‐32 <= d < MN ‐46.07 ‐41.75 ‐77.88 ‐78.09 #DIV/0! ‐39.38 ‐77.90 ‐78.12 ‐42.17 ‐46.50 ‐75.63 ‐77.57 #DIV/0! ‐45.07 ‐74.25 ‐78.55 

# 7 4 12 218 0 8 5 34 3 1 8 106 0 7 4 55 

MX < d <= MX+32 74.87 77.37 71.63 143.46 74.30 74.48 72.79 141.93 75.26 74.40 83.27 141.87 75.25 73.96 82.75 142.33 

# 229 23 16 226 323 403 7 132 233 574 13 119 273 288 4 190 

d < MN‐32 ‐459.63 ‐394.46 ‐383.80 ‐168.39 ‐813.75 ‐1322.07 ‐577.41 ‐737.39 ‐354.96 ‐927.09 ‐417.22 ‐352.88 ‐271.13 ‐665.54 ‐667.36 ‐426.76 

# 16 12 20 121 8 88 46 89 26 44 36 69 26 48 29 84 

d > MX+32 188.48 840.64 565.05 225.24 734.78 279.22 359.31 318.11 415.31 204.98 215.11 275.20 308.08 258.39 276.55 271.75 

# 33 14 11 425 140 47 93 189 91 112 33 147 88 60 66 175 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average 21.15 23.08 ‐4.54 14.56 27.57 23.18 ‐1.61 28.38 23.27 28.33 ‐1.46 24.96 22.13 28.68 0.00 25.29 

Std Dev 19.85 25.08 22.28 50.34 68.31 85.63 37.63 60.31 36.43 48.27 24.98 41.41 26.72 37.25 32.80 49.00 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐6
x R

x L 

d <

G

R. Thumb R. Inde Middle R. Ring

No Finger Found 40 14 12 11

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐7.07 ‐7.59 ‐11.52 ‐19.57 ‐6.54 ‐5.57 ‐15.80 ‐17.18 ‐7.26 ‐5.71 ‐15.88 ‐17.82 ‐5.33 ‐6.82 ‐15.73 ‐17.92 

# 12096 12616 17457 14475 15629 7876 20638 11678 15179 9863 19934 8839 9667 11220 20074 10471 

0 <= d <= MX 6.13 8.62 4.81 35.33 5.29 6.98 6.57 16.67 5.91 6.44 6.47 20.28 6.06 6.50 6.31 22.44 

# 11914 11257 6741 8368 9269 17040 4293 13139 9749 15053 5001 15852 15268 13556 4854 14231 

MN‐32 <= d < MN ‐39.94 ‐40.53 ‐79.98 ‐77.67 ‐38.57 ‐41.00 ‐73.93 ‐77.35 ‐38.13 ‐38.40 ‐73.92 ‐76.12 ‐39.33 ‐38.71 ‐73.09 ‐76.63 

# 36 87 45 426 53 33 15 99 24 35 13 178 12 172 22 163 

MX < d <= MX+32 70.50 76.53 77.65 144.35 #DIV/0! #DIV/0! #DIV/0! 143.93 #DIV/0! 72.50 #DIV/0! 140.11 69.50 86.00 #DIV/0! 140.62 

# 2 66 23 328 0 0 0 15 0 2 0 27 2 1 0 34 

d < MN‐32 ‐280.06 ‐639.22 ‐353.47 ‐420.53 ‐287.55 ‐351.25 ‐527.42 ‐383.55 ‐340.50 ‐684.83 ‐303.96 ‐183.38 ‐436.90 ‐735.79 ‐304.93 ‐204.23 

# 36 350 48 325 11 8 13 20 7 9 13 49 5 12 7 49 

d > MX+32 616.22 314.28 778.77 233.31 226.08 421.32 483.44 574.56 499.83 445.25 240.36 308.11 622.04 435.07 338.32 261.58 

# 338 46 108 500 6 11 9 17 9 6 7 23 14 7 11 20 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 7.55 ‐8.45 ‐4.23 0.27 ‐2.28 3.02 ‐12.07 0.60 ‐2.06 1.44 ‐11.51 6.10 1.89 ‐0.03 ‐11.42 4.77 

Std Dev 77.58 86.80 60.75 92.21 11.01 14.47 21.24 33.42 14.41 17.32 14.90 30.01 19.45 22.84 15.06 32.11 

L. Thumb L. Inde . Middle L. Ring

No Finger Found 31 12 13 8

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐7.46 ‐6.74 ‐12.94 ‐19.02 ‐6.24 ‐7.30 ‐16.09 ‐17.25 ‐7.74 ‐6.68 ‐15.97 ‐18.38 ‐7.79 ‐6.20 ‐15.79 ‐18.70 

# 13070 11703 18953 13174 13252 8533 20054 11636 15378 7484 19142 8999 14868 5185 18235 11293 

0 <= d <= MX 9.84 6.64 4.41 34.18 6.23 6.92 5.92 16.41 5.72 7.61 5.52 18.89 6.10 8.54 6.01 18.76 

# 10764 12306 5266 9423 11685 16194 4876 13200 9548 17396 5787 15605 10042 19700 6704 13349 

MN‐32 <= d < MN ‐41.60 ‐43.49 ‐77.00 ‐76.29 ‐40.36 ‐39.04 ‐73.75 ‐75.35 ‐39.24 ‐36.69 ‐72.08 ‐76.34 ‐37.86 ‐37.73 ‐73.60 ‐78.38 

# 62 49 74 324 14 226 20 85 17 65 12 246 36 60 10 207 

MX < d <= MX+32 76.77 76.67 78.60 144.15 84.00 #DIV/0! #DIV/0! 143.50 66.67 74.00 76.50 144.12 90.00 76.50 #DIV/0! 142.19 

# 142 3 5 505 3 0 0 14 3 1 3 26 1 2 0 32 

d < MN‐32 ‐609.11 ‐447.46 ‐276.29 ‐367.31 ‐876.50 ‐697.81 ‐508.75 ‐297.53 ‐521.83 ‐874.41 ‐367.00 ‐197.61 ‐437.75 ‐576.33 ‐516.39 ‐178.47 

# 317 53 61 232 2 8 8 18 6 11 14 52 10 6 9 60 

d > MX+32 219.88 641.40 743.33 225.49 603.94 836.67 462.75 542.73 627.33 620.86 248.50 345.22 376.43 545.14 462.83 411.20 

# 67 308 63 764 8 3 6 11 12 7 6 36 7 11 6 23 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average ‐6.61 7.16 ‐8.08 8.46 ‐0.29 1.52 ‐11.88 0.49 ‐2.42 3.00 ‐11.13 4.67 ‐2.31 5.46 ‐10.02 1.05 

Std Dev 74.74 79.28 47.54 84.45 16.92 20.36 17.62 29.21 19.51 24.83 16.08 32.69 14.57 18.00 18.17 33.89 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐7
x R

x L 

d <

H

R. Thumb R. Inde Middle R. Ring

No Finger Found 4129 44 23 25

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐6.85 ‐9.71 ‐12.28 ‐22.98 ‐4.32 ‐5.28 ‐8.59 ‐22.45 ‐5.53 ‐5.18 ‐8.65 ‐29.99 ‐4.04 ‐6.90 ‐8.03 ‐31.78 

# 2677 5766 2924 1509 11959 1737 14338 539 13558 3947 13875 705 4492 6018 12800 458 

0 <= d <= MX 15.67 12.76 21.00 36.93 9.14 16.59 12.20 43.29 8.41 13.77 12.83 47.78 12.11 11.66 13.00 49.06 

# 17541 13974 17049 17810 12839 23095 10479 24099 11222 20892 10986 23820 20372 18724 12056 23978 

MN‐32 <= d < MN ‐42.24 ‐41.44 ‐77.29 ‐78.59 ‐39.21 ‐42.02 ‐75.93 ‐78.99 ‐38.01 ‐39.03 ‐74.56 ‐78.09 ‐39.18 ‐38.44 ‐75.95 ‐78.98 

# 65 457 98 308 87 27 28 78 112 48 34 160 31 157 28 149 

MX < d <= MX+32 #DIV/0! 74.10 67.95 142.04 77.67 75.75 73.25 136.17 #DIV/0! 82.00 77.17 142.19 88.00 #DIV/0! 77.75 142.42 

# 0 10 11 141 6 4 4 24 0 2 9 85 2 0 4 104 

d < MN‐32 ‐137.11 ‐1397.95 ‐175.14 ‐1296.79 ‐294.76 ‐293.76 ‐420.48 ‐373.73 ‐327.85 ‐628.08 ‐300.00 ‐197.38 ‐322.09 ‐907.32 ‐317.70 ‐215.84 

# 18 4209 218 4498 61 50 23 185 53 24 38 142 45 25 64 133 

d > MX+32 1034.46 259.67 881.06 224.07 201.25 377.99 436.97 426.63 429.13 346.15 193.27 339.56 683.87 342.44 351.63 267.85 

# 4121 6 4122 156 16 55 96 43 23 55 26 56 26 44 16 146 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 184.84 ‐236.60 160.06 ‐212.07 1.92 15.19 1.40 39.15 0.31 10.80 0.51 44.36 9.24 6.54 1.50 47.07 

Std Dev 384.70 537.44 332.79 540.17 18.88 25.52 35.75 53.59 22.88 28.98 20.81 36.49 29.18 36.47 25.34 39.84 

L. Thumb L. Inde . Middle L. Ring

No Finger Found 251 67 24 17

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐9.27 ‐7.34 ‐12.43 ‐20.91 ‐2.95 ‐6.98 ‐8.37 ‐22.54 ‐4.78 ‐6.19 ‐8.89 ‐29.61 ‐4.56 ‐6.60 ‐7.82 ‐29.05 

# 6436 2157 3651 2344 4611 5082 13715 489 8146 5734 13545 768 10527 1951 11817 491 

0 <= d <= MX 11.26 17.73 21.24 34.33 12.64 12.81 12.94 42.76 11.39 11.59 13.10 46.11 10.24 17.27 14.26 44.84 

# 14954 19653 19455 20364 20175 19594 11045 24086 16669 19077 11294 23657 14286 22907 12996 23837 

MN‐32 <= d < MN ‐42.64 ‐43.74 ‐77.33 ‐78.11 ‐40.95 ‐39.75 ‐75.02 ‐77.40 ‐37.91 ‐38.60 ‐77.24 ‐76.85 ‐37.41 ‐40.20 ‐75.39 ‐79.70 

# 447 80 101 319 38 175 25 77 66 73 27 213 63 28 19 174 

MX < d <= MX+32 76.71 #DIV/0! 79.08 143.48 86.50 87.50 77.06 140.94 77.58 81.00 84.13 140.74 83.50 94.00 #DIV/0! 143.77 

# 42 0 401 235 1 2 9 25 6 2 8 54 9 1 0 100 

d < MN‐32 ‐849.22 ‐530.32 ‐223.72 ‐556.32 ‐103.32 ‐884.32 ‐255.77 ‐376.37 ‐422.00 ‐540.39 ‐319.73 ‐186.94 ‐292.47 ‐358.36 ‐316.60 ‐170.77 

# 2348 277 132 919 31 110 37 234 14 66 63 187 17 65 116 172 

d > MX+32 258.01 915.68 518.02 280.35 781.64 110.50 379.78 339.35 487.56 611.08 182.46 382.45 329.89 434.54 347.69 309.84 

# 195 2255 682 241 108 1 133 53 63 12 27 85 62 12 16 190 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average ‐75.78 92.01 29.30 8.81 12.87 4.47 2.72 37.91 6.96 6.19 0.44 42.34 4.49 14.56 2.42 43.44 

Std Dev 259.87 271.54 120.66 170.04 58.87 71.11 35.39 56.16 31.91 39.47 23.75 40.58 22.03 26.41 29.69 41.89 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐8
x R

L. 

d <

I

R. Thumb R. Inde Middle R. Ring

No Finger Found 27 127 12 18

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐9.79 ‐9.66 ‐16.49 ‐18.31 ‐8.48 ‐7.24 ‐12.63 ‐15.60 ‐6.47 ‐7.81 ‐12.35 ‐20.78 ‐7.23 ‐8.81 ‐13.32 ‐20.49 

# 56 374 626 5931 381 345 259 1331 343 550 252 2088 122 1183 219 977 

0 <= d <= MX 37.35 32.14 28.94 27.65 18.23 20.67 23.04 27.67 17.22 18.74 23.13 31.84 20.05 18.63 23.69 33.97 

# 24107 23572 22621 17538 24372 24368 24409 23102 24523 24302 24609 22167 24726 23549 24603 23184 

MN‐32 <= d < MN ‐45.29 ‐44.95 ‐79.81 ‐78.07 ‐41.33 ‐44.20 ‐81.50 ‐76.88 ‐44.00 ‐40.33 ‐86.14 ‐79.16 ‐54.23 ‐37.36 ‐80.40 ‐81.94 

# 21 57 27 319 3 10 4 26 6 6 7 159 13 22 5 95 

MX < d <= MX+32 72.09 75.99 75.73 141.63 77.30 71.33 70.87 143.05 72.91 79.00 72.55 143.13 76.00 77.51 71.15 143.64 

# 23 168 724 150 15 6 54 134 11 13 31 231 3 96 26 297 

d < MN‐32 ‐261.44 ‐393.20 ‐195.99 ‐524.44 ‐366.23 ‐350.05 ‐261.42 ‐670.17 ‐293.40 ‐359.36 ‐285.89 ‐245.10 ‐235.92 ‐678.32 ‐417.22 ‐270.95 

# 96 85 53 367 53 184 12 246 59 29 14 129 72 33 81 97 

d > MX+32 417.50 279.47 532.29 236.25 182.73 387.80 463.36 218.79 292.75 263.20 243.18 218.88 588.95 233.46 303.76 258.87 

# 119 166 371 117 144 55 230 129 26 68 55 194 32 85 34 318 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average 37.88 31.82 36.21 8.51 17.98 18.34 26.68 19.98 16.46 18.40 23.11 27.79 19.87 17.32 22.35 34.39 

Std Dev 41.27 49.32 79.48 88.90 24.27 38.75 47.56 81.95 21.43 23.16 19.35 41.64 29.26 36.96 32.13 47.65 

L. Thumb L. Index Middle L. Ring

No Finger Found 33 122 7 30

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐9.73 ‐8.45 ‐16.02 ‐17.89 ‐7.93 ‐9.23 ‐12.76 ‐14.78 ‐6.27 ‐8.00 ‐11.40 ‐20.68 ‐6.19 ‐9.48 ‐16.10 ‐18.33 

# 270 93 557 5830 114 1093 249 1486 245 767 316 2316 315 356 131 1484 

0 <= d <= MX 33.48 34.43 29.17 27.23 19.38 19.94 23.59 27.59 18.54 19.78 23.49 31.63 18.19 22.11 24.92 30.91 

# 23479 24074 21527 17585 24641 23644 24501 22993 24601 24092 24566 21931 24439 24478 24700 22684 

MN‐32 <= d < MN ‐47.64 ‐46.14 ‐75.67 ‐78.16 #DIV/0! ‐43.23 ‐72.75 ‐80.28 ‐64.00 ‐46.21 ‐81.80 ‐78.47 ‐39.33 ‐48.47 ‐83.33 ‐79.97 

# 36 14 12 300 0 13 8 36 1 14 5 206 3 17 3 115 

MX < d <= MX+32 75.15 70.50 77.31 142.55 74.00 76.90 74.83 142.33 76.48 74.31 80.50 141.81 76.99 70.75 79.50 142.59 

# 366 8 1570 209 7 10 12 118 29 16 8 189 80 4 5 256 

d < MN‐32 ‐185.72 ‐316.93 ‐274.12 ‐555.86 ‐319.48 ‐1170.40 ‐216.83 ‐690.67 ‐423.48 ‐449.59 ‐335.03 ‐216.36 ‐294.53 ‐363.18 ‐423.40 ‐289.46 

# 63 123 34 373 49 151 9 201 27 50 32 138 19 90 84 127 

d > MX+32 226.38 345.93 351.81 264.86 965.89 309.18 472.88 236.31 356.94 526.28 274.51 253.33 253.95 407.00 322.49 273.61 

# 208 110 722 125 153 53 185 130 61 25 37 184 108 19 41 298 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average 34.59 33.87 40.30 8.46 24.41 12.07 26.46 20.76 18.71 18.49 22.96 26.96 18.85 20.53 23.68 29.88 

Std Dev 28.24 40.41 85.47 95.91 81.21 101.29 44.39 76.97 29.03 35.03 21.46 43.14 24.09 32.24 34.11 52.05 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐9
x R

x L 

d <

J

R. Thumb R. Inde Middle R. Ring

No Finger Found 75 3 13 57

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐13.04 ‐14.27 ‐19.34 ‐25.81 ‐13.03 ‐9.98 ‐24.86 ‐20.50 ‐12.88 ‐10.38 ‐23.98 ‐20.04 ‐10.51 ‐11.14 ‐23.77 ‐17.57 

# 21888 19631 23619 10289 20800 19165 24008 6841 21255 19377 23838 4907 21321 16478 23816 4659 

0 <= d <= MX 3.14 12.31 2.31 58.29 17.54 8.75 5.27 80.60 9.59 11.26 4.69 88.14 5.41 18.44 5.04 82.07 

# 2043 3757 399 9787 3013 4717 651 2980 2962 4807 831 4974 2523 6953 779 4722 

MN‐32 <= d < MN ‐38.98 ‐40.48 ‐76.06 ‐71.01 ‐42.62 ‐44.48 ‐76.61 ‐77.05 ‐43.84 ‐40.43 ‐77.23 ‐78.60 ‐46.21 ‐41.42 ‐77.90 ‐79.67 

# 360 735 178 2062 364 457 85 211 393 209 66 166 480 386 59 113 

MX < d <= MX+32 #DIV/0! 76.38 #DIV/0! 142.73 79.42 79.12 87.00 144.90 76.00 79.27 79.07 144.21 79.13 77.56 87.31 144.49 

# 0 84 0 1144 410 186 3 3535 31 213 7 4369 23 559 18 4187 

d < MN‐32 ‐199.55 ‐477.01 ‐160.51 ‐384.96 ‐130.09 ‐100.19 ‐603.05 ‐135.98 ‐252.30 ‐289.38 ‐572.61 ‐170.59 ‐148.29 ‐516.91 ‐567.07 ‐300.44 

# 70 181 142 381 100 185 120 104 205 92 222 108 415 190 188 152 

d > MX+32 827.30 211.07 892.57 186.95 124.78 341.16 205.33 206.88 281.99 293.32 218.63 208.81 425.64 187.78 179.43 208.50 

# 61 34 84 759 281 258 101 11297 122 270 4 10444 206 402 108 11135 

Total # 24422 24422 24422 24422 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 24968 

Average ‐10.51 ‐13.77 ‐17.09 12.98 ‐7.18 ‐3.45 ‐26.08 116.90 ‐11.11 ‐3.45 ‐27.98 124.94 ‐8.19 ‐2.03 ‐26.13 127.27 

Std Dev 45.71 64.21 58.04 104.24 25.05 46.93 50.79 108.34 38.55 45.59 66.62 105.74 53.49 66.70 56.45 105.83 

L. Thumb L. Inde . Middle L. Ring

No Finger Found 9 657 71 12

L R T B L R T B L R T B L R T B 

MN <= d < 0 ‐13.79 ‐12.93 ‐21.04 ‐27.17 ‐12.31 ‐10.13 ‐23.96 ‐20.31 ‐12.94 ‐9.47 ‐23.06 ‐20.44 ‐13.37 ‐8.38 ‐22.19 ‐20.14 

# 19573 21510 23898 9142 19989 17032 23708 5656 19843 17622 23714 4468 17139 16697 23548 5099 

0 <= d <= MX 16.30 3.13 2.48 59.71 12.11 11.96 2.41 86.17 13.38 6.98 3.16 89.03 22.05 4.10 8.84 86.59 

# 4018 2453 257 10466 3109 5706 431 2926 3896 6127 482 5350 6101 6725 724 5246 

MN‐32 <= d < MN ‐40.25 ‐40.27 ‐77.98 ‐70.19 ‐46.89 ‐41.97 ‐75.70 ‐78.31 ‐41.52 ‐41.83 ‐74.27 ‐78.88 ‐40.43 ‐44.74 ‐76.71 ‐79.45 

# 514 323 115 2212 508 643 60 135 162 354 44 185 112 554 28 156 

MX < d <= MX+32 75.80 #DIV/0! 82.50 142.75 78.88 79.14 92.00 144.88 77.71 75.61 80.25 144.40 77.04 78.80 81.73 144.41 

# 148 0 1 1379 233 501 2 3795 189 31 18 4596 605 15 121 4327 

d < MN‐32 ‐270.92 ‐225.14 ‐275.62 ‐237.00 ‐99.10 ‐1256.62 ‐580.19 ‐738.35 ‐332.49 ‐511.45 ‐344.19 ‐275.43 ‐325.08 ‐132.16 ‐584.25 ‐189.41 

# 116 101 121 242 317 719 97 719 632 157 667 178 674 224 149 125 

d > MX+32 178.33 784.73 772.67 205.21 924.43 129.03 379.73 205.78 320.12 348.77 173.03 215.71 144.39 360.06 149.23 205.65 

# 53 35 30 981 808 363 666 11733 242 673 39 10187 333 749 394 10011 

Total # 24422 24422 24422 24422 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 24964 

Average ‐9.66 ‐11.42 ‐21.34 23.01 20.10 ‐37.99 ‐15.01 102.55 ‐13.19 0.72 ‐30.84 127.48 ‐8.96 4.17 ‐21.50 120.14 

Std Dev 32.87 37.90 40.25 87.40 180.79 221.32 78.93 179.46 70.20 81.42 65.47 112.13 62.14 69.71 57.99 101.54 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

C‐10
Appendix D. Plots of 3-inch segmentation box centers. 

The plots in this appendix show the distribution of the segmentation box centers 

(x,y) for the 3-inch data. There is a combined plot for each slap image and then a 

smaller plot for each finger position. The individual finger plots are better for 

seeing the full “spread” of x,y positions detected. The plot for the ground truth 

(GT) is included as a baseline for comparison. The blank lines that appear in 

some of the plots are most likely caused by the segmentation algorithm doing 

some level of sampling of the input image. The reason the lines are not evenly 

distributed in some plots is an artifact of the sampling when scaling the images 

for displaying in the report. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐1
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐2
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐3
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐4
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐5
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐6
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐7
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐8
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐9
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐10
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐11
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐12
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐13
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐14
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐15
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐16
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐17
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐18
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐19
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐20
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐21
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐22
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐23
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐24
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐25
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐26
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐27
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐28
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐29
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐30
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐31
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐32
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

D‐33
Appendix E. Plots of 3-inch segmentation box widths and heights. 

The plots in this appendix show the distribution of the segmentation box widths 

and heights for the 3-inch data. There is a combined plot for each slap image 

and then a smaller plot for each finger position. The individual finger plots are 

better for seeing the full “spread” of widths and heights detected. The widths are 

“spread out” on the plot by adding 350, 750 and 1050 to the 2nd, 3rd, and 4th

widths plotted. The plot for the ground truth (GT) is included as a baseline for 

comparison. The blank lines that appear in some of the plots are most likely 

caused by the segmentation algorithm doing some level of sampling of the input 

image. The reason the lines are not evenly distributed in some plots is an artifact 

of the sampling when scaling the images for displaying in the report. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐1
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐2
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐3
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐4
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐5
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐6
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐7
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐8
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐9
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐10
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

E‐11
Appendix F. Plots of 2-inch segmentation box centers. 

The plots in this appendix show the distribution of the segmentation box centers 

(x,y) for the 2-inch data. There is a combined plot for each slap image and then a 

smaller plot for each finger position. The individual finger plots are better for 

seeing the full “spread” of x,y positions detected. The plot for the ground truth 

(GT) is included as a baseline for comparison. The blank lines that appear in 

some of the plots are most likely caused by the segmentation algorithm doing 

some level of sampling of the input image. The reason the lines are not evenly 

distributed in some plots is an artifact of the sampling when scaling the images 

for displaying in the report. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐1
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐2
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐3
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐4
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐5
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐6
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐7
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐8
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐9
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐10
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐11
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐12
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐13
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐14
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐15
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐16
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐17
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐18
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐19
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

F‐20
Appendix G. Plots of 2-inch segmentation box widths and heights. 

The plots in this appendix show the distribution of the segmentation box widths 

and heights for the 2-inch data. There is a combined plot for each slap image 

and then a smaller plot for each finger position. The individual finger plots are 

better for seeing the full “spread” of widths and heights detected. The widths are 

“spread out” on the plot by adding 350, 750 and 1050 to the 2nd, 3rd, and 4th

widths plotted. The plot for the ground truth (GT) is included as a baseline for 

comparison. The blank lines that appear in some of the plots are most likely 

caused by the segmentation algorithm doing some level of sampling of the input 

image. The reason the lines are not evenly distributed in some plots is an artifact 

of the sampling when scaling the images for displaying in the report. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
G‐1
G‐2
G‐3
G‐4
G‐5
G‐6
G‐7
G‐8
G‐9
G‐10
Appendix H. Confidence intervals for 3-inch segmentation results. 

The plots in this appendix are an attempt to show 95% confidence intervals for 

the 3-inch segmentation results shown in tables in Appendix A for the finger 

positions and right/left hands. The confidence intervals were computed using the 

boot strap function in the R statistics package and a sampling of 1,000 iterations. 

The only issue is that the intervals were so small that they really don’t show well 

in the plots. The plots are shown on two scales. The first shows the results for all 

the segmentation algorithms. The second shows only results in the range 90-

100% correct segmentation. The “None” segmented is not included in the second 

plot just to make it easier to read. 

A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐1
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐2
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐3
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐4
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐5
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐6
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐7
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐8
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐9
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐10
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐11
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐12
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐13
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐14
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

H‐15
A = Aware || B/C = Cogent || D = Dermalog || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan 

Appendix I. Confidence intervals for 2-inch segmentation results. 

The plots in this appendix are an attempt to show 95% confidence intervals for 

the 2-inch segmentation results shown in tables in Appendix B for the finger 

positions and right/left hands. The confidence intervals were computed using the 

boot strap function in the R statistics package and a sampling of 1,000 iterations. 

The only issue is that the intervals were so small that they really don’t show well 

in the plots. The plots are shown on two scales. The first shows the results for all 

the segmentation algorithms. The second shows only results in the range 90-

100% correct segmentation. The “None” segmented is not included in the second 

plot just to make it easier to read. 
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

I‐1
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

I‐2
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

I‐3
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

I‐4
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

I‐5
A = Aware || B/C = Cogent || E/F = NEC || G = Sagem Morpho || H/I = Sonda || J = Ultrascan

I‐6