NISTIR 7201

Effect of Image Size and Compression 

on One-to-One Fingerprint Matching

Craig Watson

Charles Wilson

 
NISTIR 7201

Effect of Image Size and Compression 

on One-to-One Fingerprint Matching 

Craig Watson

Charles Wilson

Information Technology Laboratory

Information Access Division

February 2005

U.S. DEPARTMENT OF COMMERCE

Carlos M. Gutierrez, Secretary

TECHNOLOGY ADMINISTRATION

Michelle O’Neill, Acting Under Secretary of Commerce for Technology

NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY

William A. Jeffrey, Director

 
Effect of Image Size and Compression on 

One-to-One Fingerprint Matching 

Craig Watson and Charles Wilson

National Institute of Standards and Technology 

Abstract 

NIST has conducted testing of one-to-one fingerprint matching systems to evaluate the effect of 

image size and compression on the accuracy of the one-to-one matching process. Images from 

three live-scan fingerprint scanners collected by the Departments of State and Homeland 

Security were used as test samples. Image sizes from 368 pixels by 368 pixels down to 180 

pixels by 180 pixels were tested and compression ratios from no compression up to 30:1 were 

tested. Three commercial fingerprint-matching systems were used in the test. The results of the 

study show that image cropping quickly degrade matcher performance. Compression degrades 

matcher performance more slowly and may increase performance for compression ratios of up to 

15:1. The conclusion from this study is that Image sizes below 320 pixels by 320 pixels should 

not be used. Image compression in the range up 20:1 produces minimal negative effects on 

fingerprint matching accuracy. 

2
Introduction 

On February 4, 2003 a report titled “Use of Technology Standards and Interoperable 

Databases With Machine-Readable, Tamper-Resistant Travel Documents” [1] was submitted to 

the Congress jointly by the Attorney General, Secretary of State, Department of Homeland 

Security and NIST . (This report is informally referred to as the 303A Report and was mandated 

by [2] and [3]). It discusses measurements of the accuracy of both face and fingerprints as they 

relate to U.S. border entry and exit. This study is part of the work undertaken under the Patriot 

Act to measure the one-to-one accuracy of fingerprint matching systems using fingerprint images 

of different sizes and varying amount of image compression. The effect of image size and 

compression ratio on fingerprint matching accuracy is important because it determines the 

amount of memory and bandwidth needed for biometrically enabled travel documents.

The results of the one-to-one fingerprint-matching tests performed at NIST using vendor 

supplied SDK libraries are discussed in [4]. The matching systems used in [4] were supplied by 

several vendors including all highly ranked vendors in the FpVTE fingerprint test [5]. This 

report contains results from three different vendors including the vendor currently used in the 

US-VISIT system. This test used data that was randomly selected from the DOS-C, POE, and 

NIST SD29 datasets. These different datasets are discussed below or in references [4,6]. 

Test Design 

The goal of this test was to determine the smallest compressed fingerprint image size that 

could be used to provide satisfactory matching accuracy. The maximum size of the images 

obtained from fingerprint scanners for single finger live scan was 368 by 368 pixels.These 

images were centered and cropped using software based on the NFIS [7] package. The cropped 

image sizes used, in pixels, were 320 by 320, 280 by 280, 200 by 200 and 180 by 180. One set of 

cropped images was used in the test without compression. Other sets of cropped images were 

compressed using the WSQ (Wavelet Scalar Compression) implementation from [7] at ratios of 

15, 20, 25, and 30 to one. 

The criteria used to evaluate matching accuracy is the TAR (True Accept Rate) at a fixed 

FAR (False Accept Rate) of 0.001. This is near the current operating point of the US-VISIT 

system and is therefore reasonable for BioVisa applications. The criterion used in selecting 

acceptable image size and compression ratio was a reduction in TAR of 0.01. This reduction is 

comparable to the reductions seen from other expected fluctuations in image quality for good 

quality images. Sufficient data is included in the appendices for the evaluation of the effects of 

image size and compression at other operating points. 

3
Testing 

Three SDK matchers were used in these tests. The matchers used were F, H, and J1

 from 

reference [4]. All testing was performed by NIST staff on NIST owned computers. The systems 

used for testing were dual-processor (3 GHz) PCs running windows 20001

. This allowed the 

SDK to run on several different datasets in parallel. All results were scored with the software 

package used in the VTB report [6]. 

Evaluation Data 

The fingerprint datasets used to evaluate the one-to-one matchers included plain fingerprints 

from inked paper and live-scan devices. The data is from several sources: Department of State 

(DOS-C), Department of Homeland Security (VISIT_POE), and NIST Special Database 29 

(SD29). SD29 is the only database available to the public. 

Random samples of 6,000 subjects were selected from the larger datasets (DOS-C, and POE). 

All the subjects that did not have segmentation problems were used in the smaller dataset 

(SD29). The datasets were consolidated to find previously unknown mates and presumed mates 

that were not actual mates. Consolidation used the output of various matches to help identify 

potential errors and then human experts examined those fingerprints to make a final 

determination. The human experts are fingerprint examiners with over twenty years of 

experience. Since DHS2-C was consolidated after testing had started, the final dataset size after 

consolidation was only 5,888 not 6,000. The images in SD29 was all segmented with the NIST 

segmentor as discussed in the VTB report [4]. The details of the consolidation process are given 

in [8]. 

DOS-C contains live-scan plain impressions of the left and right index fingers. They were 

captured in an operational office environment. DOS-C fingerprints should give results typical of 

real time data of plain to plain (P2P) impression matching. SD29 contained ten-print card mates 

of inked paper segmented plain and rolled impressions (P2P, R2R, P2R). The dataset is from

legacy inked paper data. The VISIT_POE data set was captured under operational condition at 

POE (Points of Entry) from travelers entering the US under the VISIT program. The fingerprints 

used in this study were primarily captured at airports. 

 

1

 

These tests were performed for the Department of Homeland Security in accordance with section 

303 of the Border Security Act, codified at 8 U.S.C. 1732. Specific hardware and software 

products identified in this report were used in order to adequately support the development of 

technology to conduct the performance evaluations described in this document. In no case does 

such identification 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. 

4
Department of State Mexican Visa Database (DOS-C) 

Department of State Mexican Visa Database (DOS-C) 

Description 

DOS Mexican Visa cases 

Environment: Mexican Consulates offices 

Number of Subjects 

~274,000 (of 288,000) 

~6 million Background 

Instances per Subject 

Minimum of 2 cases per person, 

where each case contains one 

right index impression and one left

index impression. 

Impression Type

Live-scan 

Plain 

Finger Positions Captured 

Right and left index fingers 

Capture Device(s) 

DFR-90 

Availability

Government use only 

Data Preparation 

Include clean up steps – e.g. mate validation and mismatch detection. [8] 

NIST Special Database 29 (SD29) 

NIST Special Database 29 (SD29) 

Description 

FBI Deceased Criminal File 

Number of Subjects 

216 

Instances per Subject 

2 fingerprint cards per person 

Impression Type

Inked 

Rolled & Plain 

Finger Positions Captured 

10 finger positions segmented 

from rolled impressions on 10-print 

card, and 10 additional finger 

positions segmented from fourfinger plain impressions on same 

10-print card 

Capture Device(s) 

UMAX PowerLook III flatbed 

scanner 

Availability

Public 

Data Preparation 

Segmentation failures of the four-finger plain impressions were manually 

inspected and corrected to enable maximum yield 

5
U.S. VISIT Point of Entry Data (VISIT_POE)

U.S. VISIT Point of Entry Data (VISIT_POE) 

Description 

Data from U.S. VISIT captured from persons entering the U.S. at airport points of entry. 

Number of Subjects 

~1.3 Million with one instance 

~106K with 2 or more instances 

Instances per Subject 

One to many cases per person, with each 

case containing one right index finger 

impression and one left index finger 

impression. 

Impression Type 

Live-scan Plain 

Finger Positions Captured

Right and Left Index 

Capture Device(s)

Cross Match 300A 

Availability

Government use only 

Data Preparation 

All cases used in the report were consolidated using matchers and human examiners. 

Results

Appendix A, B, and C each contains 20 sets of ROC plots for each of the F, H, and J SDKs 

used in the test. The first test conducted was an analysis of the effect of image cropping on DOSC images that were compressed at a ratio 15:1. All images were cropped using software from [7]. 

The results of this experiment are summarized in table 1. Similar results for US-VISIT_POE and 

SD29 are shown in tables 2 and 3. In all cases full ROC results are given in Appendix A. Greater 

weight should be given to POE and DOS-C data in these experiments since the images in these 

samples are acquired from live scan devices under operational conditions. The images in SD29 

are from scanned paper and are introduced because this dataset in was the only uncompressed 

data available for test. 

6
In all three tables the maximum TAR for 368 pixel images is a strong function of the image 

quality of the data set. POE data has the best image quality followed by DOS-C. The effect of 

image quality on matcher performance is discussed in detail in [9]. SD29 has the worst image 

quality. If a criteria of a 0.01 drop in TAR at a FAR of 0.001 is applied to both right and left 

index fingers, image sizes below 320 pixels can not be allowed. The drop of 0.022 in right finger 

SD29 TAR is discounted in reaching this conclusion because of the small sample size and 

relatively poor image quality. These tables also show that even with a high quality commercial 

fingerprint matcher such as SDK-F small images such as the 180 pixel images would result in a 

0.144 reduction in TAR which would place the fingerprint matching results far outside the 

required performance needed for most applications. 

Image Size Right finger Left finger

368 0.986 0.969

320 0.981 0.959

280 0.972 0.944

200 0.839 0.764

180 0.762 0.688

Table 1: TARs at FAR of 0.001 for DOS-C right and left index fingers as a function of center 

cropped image size. All images were compressed at 15:1. 

Image Size Right finger Left finger

368 0.993 0.986

320 0.990 0.982

280 0.985 0.977

200 0.908 0.888

180 0.847 0.832

 

Table 2: TARs at FAR of 0.001 for POE right and left index fingers as a function of center 

cropped image size. All images were compressed at 15:1. 

Image Size Right finger Left finger

368 0.959 0.963

320 0.937 0.968

280 0.940 0.947

200 0.696 0.708

180 0.650 0.644

Table 3: TARs at FAR of 0.001 for SD29 right and left index fingers as a function of center 

cropped image size. All images were compressed at 15:1. 

7
The effects of different compression ratios are shown for 320 pixel and 368 pixel images in 

tables 4 and 5 for US-VISIT POE images. The effect of compression ratios for SD29 data are 

shown in tables 6 and 7. As above the SDK-F matcher was used for all tests. In all cases full 

ROC results are given in Appendix A. It must be noted that compression ratios greater than 16:1 

in tables 4 and 5 were calculated by decompressing data which had been compressed (~15:1) at 

original capture and recompressing at 20:1` and 25:1. This accounts for at least part of change in 

TAR between the 15:1 and 20:1 lines in these tables. 

Compression 

Ratio 

Right finger Left finger

15 0.990 0.982

20 0.983 0.972

25 0.978 0.970

Table 4: TARs at FAR of 0.001 for right and left index fingers as a function of image 

compression ratio for 320 pixel images from the POE data set. 

Compression 

Ratio 

Right finger Left finger

15 0.993 0.986

20 0.988 0.979

25 0.985 0.979

30 0.982 0.975

Table 5: TARs at FAR of 0.001 for right and left index fingers as a function of image 

compression ratio 368 pixel images from the POE data set. 

. 

Compression 

Ratio 

Right finger Left finger

00 0.947 0.964

15 0.959 0.963

20 0.954 0.974

25 0.963 0.968

30 0.944 0.957

Table 6: TARs at FAR of 0.001 for right and left index fingers as a function of image 

compression ratio 368 pixel images from the SD29 data set. 

8
. 

Compression 

Ratio 

Right finger Left finger

00 0.949 0.957

15 0.937 0.968

20 0.935 0.963

25 0.932 0.956

30 0.929 0.942

Table 7: TARs at FAR of 0.001 for right and left index fingers as a function of image 

compression ratio 320 pixel images from the SD29 data set. 

 When SD29 results are examined, a rise in TAR between uncompressed data and 15:1 

compressed data is seen for both 368 pixel right finger and 320 pixel left fingerprint images. 

This is a common effect widely observed in fingerprint matching experiments. This effect is due 

to the fact that the WSQ algorithm used in fingerprint compression reduces the high frequency 

noise in the image and improves matcher performance. 

These tables show that compression beyond 20:1 will cause the decrease in TAR to exceed the 

specified value of 0.01.The degradation in performance with compression is much less abrupt 

than that caused by reducing image size. 

. 

Conclusions 

The results of the study show that image cropping quickly degrades matcher performance. 

Compression degrades matcher performance more slowly and may, for compression ratios of up 

to 15:1, increase performance. Image sizes below 320 pixels by 320 pixels should not be used 

due to poor matching performance. Image compression in the range up 20:1 produces minimal 

effects on fingerprint matching accuracy. In size critical applications, increasing compression 

will have less impact on matcher performance than decreasing image size.

9
References 

[1] “Summary of NIST Standards for Biometric Accuracy, Tamper Resistance, and 

Interoperability,” PDF document at http://www.itl.nist.gov/iaui/894.03/fing/fing.html, November 

2002. 

[2] Public Law 107-56 (USA PATRIOT ACT); 107th United States Congress, Washington, D.C.; 

26 October 2001 

[3] Public Law 107-173 (Enhanced Border Security and Visa Entry Reform Act of 2002); 107th

United States Congress, Washington, D.C.; 14 May 2002 

[4] C. Watson, A. Wilson, K. Marshall, M. Indovina, R. Snelick. “Studies of one-to-one 

fingerprint matching with vendor SDK matchers,” NISTIR 7119 at 

http://fingerprint.nist.gov/SDK/ir_7119.pdf

[5] Charles Wilson, R. Austin Hicklin, Harold Korves, Bradford Ulery, Melissa Zoepfl, Mike 

Bone, Patrick Grother, Ross Micheals, Steve Otto, and Craig Watson,“Fingerprint Vendor 

Technology Evaluation 2003,” NISTIR 7123, June 2004 at 

http://fpvte.nist.gov/report/ir_7123_summary.pdf

[6] C L Wilson, C I Watson, M D Garris, A Hicklin; “Studies of Fingerprint Matching Using the 

NIST Verification Test Bed (VTB)” NIST IR 7020; National Institute of Standards and 

Technology; Gaithersburg Maryland , 07 July 2003 at 

ftp://sequoyah.nist.gov/pub/nist_internal_reports/ir_7020.pdf

[7] M.D. Garris, C.I. Watson, R.M. McCabe, C.L. Wilson. “User’s guide to NIST fingerprint 

image software.” NISTIR 6813. http://fingerprint.nist.gov/NFIS 

[8] C. L. Wilson, M.D. Garris, C.I. Watson. “Matching performance for the US-VISIT IDENT 

system using flat fingerprints, NIST IR 7110”, May 2004 at 

http://www.itl.nist.gov/iad/894.03/pact/pact.html

[9] E. Tabassi, C. L. Wilson, and C. I. Watson, “Fingerprint Image Quality” NIST IR 

7152, August 2004, at 

ftp://sequoyah.nist.gov/pub/nist_internal_reports/ir_7151/ir_7151.pdf . 

10
APPENDIX A: ROC CURVES FOR MATCHER F 

Figure F1: ROC plots for POE left index fingers using 15:1 compression for different image 

sizes. 

Figure F2: ROC plots for POE right index fingers using 15:1 compression for different image 

sizes. 

A-1
Figure F3: ROC plots for POE left index fingers using 320 by 320 images at different 

compressions ratios. 

Figure F4: ROC plots for POE right index fingers using 368 by 368 images at different 

compressions ratios. 

A-2
Figure F5: ROC plots for POE left index fingers using 320 by 320 images at different 

compressions ratios. 

Figure F6: ROC plots for POE right index fingers using 320 by 320 images at different 

compressions ratios. 

A-3
Figure F7: ROC plots for SD29 left index fingers using different image sizes for uncompressed 

data. 

Figure F8: ROC plots for SD29 right index fingers using different images sizes and no 

compression. 

A-4
Figure F9: ROC plots for SD29 left index fingers using different images sizes and 15:1 

compression. 

Figure F10: ROC plots for SD29 right index fingers using different images sizes and 15:1 

compression. 

A-5
Figure F11: ROC plots for SD29 left index fingers using different images sizes and 20:1 

compression. 

Figure F12: ROC plots for SD29 right index fingers using different images sizes and 20:1 

compression. 

A-6
Figure F13: ROC plots for SD29 left index fingers using different images sizes and 25:1 

compression. 

Figure F14: ROC plots for SD29 right index fingers using different images sizes and 25:1 

compression. 

A-7
Figure F15: ROC plots for SD29 left index fingers using different images sizes and 30:1 

compression. 

Figure F16: ROC plots for SD29 right index fingers using different images sizes and 30:1 

compression. 

A-8
Figure F17: ROC plots for SD29 left index fingers using different compression ratios for 320 

pixel image. 

Figure F18: ROC plots for SD29 right index fingers using different compression ratios for 320 

pixel images. 

A-9
Figure F19: ROC plots for SD29 left index fingers using different compression ratios for 368 

pixel images. 

Figure F20: ROC plots for SD29 right index fingers using different compression ratios for 368 

pixel images. 

A-10
APPENDIX B: ROC CURVES FOR MATCHER H 

Figure H1: ROC plots for POE left index fingers using 15:1 compression for different image 

sizes. 

Figure H2: ROC plots for POE right index fingers using 15:1 compression for different image 

sizes. 

B-1
Figure H3: ROC plots for POE left index fingers using different compression for 368 images. 

Figure H4: ROC plots for POE right index fingers using different compression for 368 

images. 

B-2
Figure H5: ROC plots for POE left index fingers using different compression for 320 images. 

Figure H6: ROC plots for POE right index fingers using different compression for 320 

images.

B-3
Figure H7: ROC plots for SD29 left index fingers using different image sizes for 

uncompressed data. 

Figure H8: ROC plots for SD29 right index fingers using different image sizes for 

uncompressed data. 

B-4
Figure H9: ROC plots for SD29 left index fingers using different image sizes for 15:1 

compression. 

Figure H10: ROC plots for SD29 right index fingers using different image sizes for 15:1 

compression. 

B-5
Figure H11: ROC plots for SD29 left index fingers using different image sizes for 20:1

compression. 

Figure H12: ROC plots for SD29 right index fingers using different image sizes for 20:1 

compression. 

B-6
Figure H13: ROC plots for SD29 left index fingers using different image sizes for 25:1

compression. 

Figure H14: ROC plots for SD29 right index fingers using different image sizes for 25:1 

compression. 

B-7
Figure H15: ROC plots for SD29 left index fingers using different image sizes for 30:1

compression. 

Figure H16: ROC plots for SD29 right index fingers using different image sizes for 30:1 

compression. 

B-8
Figure H17: ROC plots for SD29 left index fingers using different compression ratios for 320 

pixel images. 

Figure H18: ROC plots for SD29 right index fingers using different compression ratios for 

320 pixel images. 

B-9
Figure H19: ROC plots for SD29 left index fingers using different compression ratios for 368 

pixel images. 

Figure H20: ROC plots for SD29 right index fingers using different compression ratios for 

368 pixel images.

B-10
APPENDIX C: ROC CURVES FOR MATCHER J 

Figure J1: ROC plots for POE left index fingers using 15:1 compression for different 

image sizes.

Figure J2: ROC plots for POE right index fingers using 15:1 compression for different 

image sizes.

C-1
Figure J3: ROC plots for POE left index fingers using different compression ratios for 

368 images. 

Figure J4: ROC plots for POE right index fingers using different compression ratios for 

368 images. 

C-2
Figure J5: ROC plots for POE left index fingers using different compression ratios for 

320 images. 

Figure J6: ROC plots for POE right index fingers using different compression ratios for 

320 images. 

C-3
Figure J7: ROC plots for SD29 left index fingers using different images sizes for 

uncompressed data. 

Figure J8: ROC plots for SD29 right index fingers using different images sizes for 

uncompressed data. 

C-4
Figure J9: ROC plots for SD29 left index fingers using different images sizes for 15:1 

compression. 

Figure J10: ROC plots for SD29 right index fingers using different images sizes for 15:1 

compression. 

C-5
Figure J11: ROC plots for SD29 left index fingers using different images sizes for 20:1 

compression. 

Figure J12: ROC plots for SD29 right index fingers using different images sizes for 20:1 

compression. 

C-6
Figure J13: ROC plots for SD29 left index fingers using different images sizes for 25:1 

compression. 

Figure J14: ROC plots for SD29 lright index fingers using different images sizes for 25:1 

compression. 

C-7
Figure J15: ROC plots for SD29 left index fingers using different images sizes for 30:1 

compression. 

Figure J16: ROC plots for SD29 right index fingers using different images sizes for 30:1 

compression. 

C-8
Figure J17: ROC plots for SD29 left index fingers using different compression ratios for 

320 pixel images. 

Figure 

J18: ROC plots for SD29 right index fingers using different compression ratios for 320 

pixel images. 

C-9
Figure J19: ROC plots for SD29 left index fingers using different compression. ratios for 

368 pixel images. 

Figure J20: ROC plots for SD29 right index fingers using different compression. ratios 

for 368 pixel images.

C-10