NIST Special Publication 1151

Markup Instructions for Extended 

Friction Ridge Features

Will Chapman

Austin Hicklin

George Kiebuzinski

Peter Komarinski

John Mayer-Splain

Melissa Taylor

Rachel Wallner

http://dx.doi.org/10.6028/NIST.SP.1151
NIST Special Publication 1151

Markup Instructions for Extended 

Friction Ridge Features

Melissa Taylor

Law Enforcement Standards Office

Office of Special Programs

Will Chapman

Austin Hicklin

George Kiebuzinski

John Mayer-Splain

Rachel Wallner

Noblis

Falls Church, VA

Peter Komarinski

Komarinski & Associates, LLC

Rotterdam, NY

http://dx.doi.org/10.6028/NIST.SP.1151

January 2013

U.S. Department of Commerce

Rebecca Blank, Acting Secretary

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director 
Certain commercial entities, equipment, or materials may be identified in this

document in order to describe an experimental procedure or concept adequately.

Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the

entities, materials, or equipment are necessarily the best available for the purpose. 

National Institute of Standards and Technology Special Publication 1151

Natl. Inst. Stand. Technol. Spec. Publ. 1151, 43 pages (January 2013) 

CODEN: NSPUE2
MARKUP INSTRUCTIONS FOR EXTENDED FRICTION RIDGE FEATURES

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Markup Instructions for Extended Friction Ridge Features

January 2013

This document provides instructions for latent print examiners in marking friction ridge features to maximize

consistency among examiners. This document builds upon the Extended Feature Set (EFS) defined in American 

National Standard for Information Systems: Data Format for the Interchange of Fingerprint, Facial & Other 

Biometric Information, American National Standards Institute/National Institute of Standards and Technology, 

Information Technology Laboratory (ANSI/NIST-ITL) 1-2011. These instructions include examples and specific 

guidance for latent print examiners and minimize references to technical details of the file format.

Three interrelated specifications have been designed to enable vendor-neutral latent automated friction ridge 

identification systems (AFIS) interoperability: the EFS Profile Specification; the Latent Interoperability 

Transmission Specification; and this one, the Markup Instructions for Extended Friction Ridge Features. The three 

documents define data exchange specifications for latent print interoperability and are all based on the EFS 

features in the ANSI/NIST-ITL (2011) standard.
MARKUP INSTRUCTIONS FOR EXTENDED FRICTION RIDGE FEATURES

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Contents

1 INTRODUCTION...................................................................................................................................................1

2 LATENT INTEROPERABILITY SPECIFICATIONS.......................................................................................................2

3 SEARCH STRATEGIES AND PROFILE SELECTION ...................................................................................................3

4 IMAGE-ONLY SEARCHING....................................................................................................................................6

5 FEATURES FOR FUNDAMENTAL LATENT AFIS SEARCHES ....................................................................................7

5.1 Region of interest/ROI (field 9.300) .......................................................................................................................... 7

5.2 Orientation/ORT (field 9.301) ................................................................................................................................... 8

5.3 Finger/palm/plantar position/FPP (field 9.302)......................................................................................................... 8

5.4 Pattern classification/PAT (field 9.307) ................................................................................................................... 12

5.5 Cores/COR (field 9.320) .......................................................................................................................................... 13

5.6 Deltas/DEL (field 9.321) .......................................................................................................................................... 14

5.7 Minutiae/MIN (field 9.331)..................................................................................................................................... 15

5.8 Evidence of fraud/EOF (field 9.354) ........................................................................................................................ 17

6 ADDITIONAL FEATURES USED IN LATENT AFIS SEARCHES .................................................................................18

6.1 Ridge quality/confidence map/RQM (field 9.308)................................................................................................... 18

6.2 Dots/DOT (field 9.340) and incipient ridges/INR (field 9.341).................................................................................. 25

6.3 Scars and other distinctive features/DIS (field 9.324).............................................................................................. 25

6.4 Ridge flow map/RFM (field 9.310) .......................................................................................................................... 26

6.5 Center point of reference/CPR (field 9.323)............................................................................................................ 27

6.6 Core-delta ridge counts/CDR (field 9.322)............................................................................................................... 29

6.7 Skeletonized image/SIM (field 9.372) ..................................................................................................................... 29

6.8 Minutiae ridge counts/MRC (field 9.333) and Minutiae ridge count algorithm/MRA (field 9.332)........................... 30

7 FEATURES USED IN SPECIAL CASES....................................................................................................................32

7.1 Possible lateral reversal/PLR (field 9.315) ............................................................................................................... 32

7.2 Tonal reversal/TRV (field 9.314).............................................................................................................................. 32

7.3 Possible growth or shrinkage/PGS (field 9.317)....................................................................................................... 32

8 TERMINOLOGY ..................................................................................................................................................34

9 REFERENCES ......................................................................................................................................................36

10 ACKNOWLEDGMENTS .......................................................................................................................................37
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1 Introduction

The Extended Feature Set (EFS) defined in American National Standard for Information Systems: Data Format for 

the Interchange of Fingerprint, Facial & Other Biometric Information, American National Standards 

Institute/National Institute of Standards and Technology, Information Technology Laboratory 1-2011 (ANSI/NISTITL 2011)

1

is a quantifiable, repeatable, and clear method of characterizing the information content of a friction 

ridge image (fingerprint, palmprint, or plantar). This document provides instructions specifically for latent print 

examiners in marking EFS features to maximize consistency among examiners. This document may also be used 

by feature extraction and matcher algorithm developers as a basis for their expectations as to how examiners 

mark features.

EFS is specifically designed to be used for vendor-neutral Automated Friction ridge Identification System (AFIS)

searches as well as for the interchange of latent print annotation among examiners as part of non-AFIS 

casework:

AFIS Searching

EFS is an interoperable AFIS interchange format for human-initiated searches, fully automated searches, 

data interchange among automated systems, and feedback to examiners from automated processing.

Interchange of Casework

EFS defines the information content of a single friction ridge impression as discerned by an examiner 

during analysis—or the information content and determination of a comparison of two friction ridge 

impressions as discerned by an examiner during comparison and evaluation—for archiving, interchanges 

with other examiners, validation and quality assurance processing, and quantitative analysis.

The Markup Instructions for Extended Friction Ridge Features are software implementation agnostic.

 

1

In the unlikely event there is a difference or discrepancy between ANSI/NIST-ITL and the Markup Instructions for Extended Friction Ridge Features, 

ANSI/NIST-ITL takes precedence.
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2 Latent Interoperability Specifications

Markup Instructions for Extended Friction Ridge Features is a companion document to the Latent Interoperability 

Transmission Specification (LITS) and the EFS Profile Specification, all three of which build upon ANSI/NIST-ITL

(2011). The three documents define data exchange specifications for latent print interoperability:

Latent Interoperability Transmission Specification is a system-level specification, parallel to and compatible

with the Federal Bureau of Investigation (FBI) Criminal Justice Information Services (CJIS) Electronic 

Biometric Transmission Specification (EBTS) (FBI CJIS 2011), but focuses on the definition of vendor-neutral 

latent transactions to be exchanged among disparate cross-jurisdictional AFIS systems. LITS-conformant AFIS 

systems provide the examiner with a seamless search capability for all interoperable AFIS systems. Encoding 

EFS features for searching on the examiner’s host AFIS creates a search record that may be sent to an AFIS 

operated by another jurisdiction with no or little additional markup.

EFS Profile Specification defines sets of features that are to be used in latent friction ridge AFIS searches and 

that are designed to be interoperable among AFIS from different vendors to enable cross-jurisdictional 

searches that would not otherwise be practical.

Markup Instructions for Extended Friction Ridge Features specifies a common set of instructions and data 

annotation guidelines for the markup of EFS features by latent print examiners.
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3 Search Strategies and Profile Selection 

EFS Profiles are sets of features to be used in latent friction ridge searches of automated friction ridge 

identification systems (AFIS). EFS Profiles are designed to be interoperable among AFIS systems from different 

vendors and to enable cross-jurisdictional searches that would not otherwise be practical. Multiple EFS Profiles 

are defined to allow for tradeoffs between examiner time and search accuracy; these profiles provide a range 

from image-only searches (requiring no examiner markup) through standard minutiae searches to profiles 

including skeletons or ridge counts (to maximize accuracy at the cost of additional examiner markup time). EFS 

also may be used to document latent friction ridge features documentation (e.g., for potential use in legal 

proceedings or exchange between examiners) and need not be for AFIS matching purposes. EFS Profiles are 

incorporated by reference by ANSI/NIST-ITL (2011).

EFS Profiles are grouped as follows:

Image-only

EFS Profile 0: Image-Only Profile requires no examiner markup. No examiner time is necessary for 

marking features, but accuracy may be lower than for feature-based searches. This corresponds to the 

FBI CJIS EBTS (2011) Latent Friction Ridge Image Search (LFIS) transaction.

Profiles for fundamental latent AFIS searches

EFS Profile 1: Minimal Markup Profile requires very limited examiner markup to improve the accuracy of 

image-only matching; it includes the Region of interest (ROI), Orientation, Pattern classification, Core(s),

or Delta(s).

EFS Profile 2: Quick Minutiae Search Profile includes minutiae in addition to the features in EFS Profile 1: 

Minimal Markup Profile, includes the features common to all interoperable systems, and is used by the 

FBI CJIS EBTS (2011); this profile is compatible with Department of Defense EBTS (2011), Prüm (2008), 

and Interpol INT-I (2007) requirements because the INCITS 378 (ANSI/INCITS 2004) features used by 

those standards can be losslessly translated to or from the features used in this profile.

The image is included with the features for both EFS Profile 1: Minimal Markup Profile and EFS Profile 2: 

Quick Minutiae Search Profile so that searches using these profiles can combine the image processing 

capabilities of the AFIS with feature-based search capabilities.

Additional profiles for maximized accuracy

Other EFS Profiles include features that can be used to increase search accuracy in systems that 

implement these optional profiles. These features require additional examiner time, but may optionally 

be used to maximize search accuracy (such as for critical cases or poor-quality latents). These features 

include ridge quality map, ridge flow map, center point of reference, distinctive features (e.g., scars), 

dots, incipient ridges, ridge counts, and skeletons. These profiles include EFS Profile 3: Detailed Markup

Profile, EFS Profile 10: Skeleton Profile, and EFS Profile 11: Minutiae Ridge Count Profile. (For details of 

these profiles, see the EFS Profile Specification.) EFS Profile 2: Quick Minutiae Search Profile is a subset 

of EFS Profile 3: Detailed Markup Profile so that if a target AFIS does not implement the optional 

features, searches can still be conducted using EFS Profile 2: Quick Minutiae Search Profile.
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Features used in special cases

Features that may be used in unusual circumstances include evidence of fraud (e.g., deliberate 

mutilation), possible lateral reversals (i.e., it is unclear if the print may be flipped left-for-right, such as in 

some prints on transparent tape), tonal inversion (black for white), or growth or shrinkage (e.g.,

deceased subjects with swollen or desiccated skin or comparison of adult and juvenile prints).

Features used for casework annotation

EFS Profile 90: Full Annotation Profile provides for annotation of casework, separate from the AFISspecific profiles. In addition to the features included in the AFIS-specific profiles, this profile may 

optionally include any of the extended feature set fields, such as pores; creases; ridge edge features; 

latent substrate, matrix, or processing; analysis assessment (value); or comparison determinations. This 

version of the Markup Instructions for Extended Friction Ridge Features focuses on features that are 

used for AFIS searches and does not include the additional features used for casework annotation.

EFS Profile 0: Image-Only Profile and EFS Profile 2: Quick Minutiae Search Profile are designed to be common to, 

and available across, all interoperable systems that are conformant to the EFS Profile Specification. Additional 

optional EFS profiles allow for tradeoffs between examiner markup time and search accuracy, a valuable 

consideration for systems that can make effective use of the additional features; optional EFS profiles may be 

implemented by some, but not all, AFIS systems, so use of optional profiles will depend on the specific 

arrangements between AFIS owners and users, generally defined in a Memorandum of Understanding. EFS 

profiles are incorporated by reference by ANSI/NIST-ITL (2011) and are fully compatible with the FBI CJIS EBTS

(2011).

The selection of an appropriate markup strategy allows the examiner to make effective use of the time 

necessary to mark features that are commensurate with the search accuracy needs for a specific case. Following 

the initial scanning or entry of the latent image, the examiner assesses the level of detail required for a 

successful search, based on the data content and quality as well as on the importance of the specific case at 

hand. The level of detail is used to select the appropriate search profile and its corresponding markup 

requirements. For example, image-only searches may be appropriate for low-priority cases that might not 

otherwise be searched or for backlog reduction. Some agencies may choose to use a “low-hanging-fruit” 

approach, in which they conduct initial searches using EFS Profile 0: Image-Only Profile or EFS Profile 1: Minimal 

Markup Profile but only review the first one or two candidates so that easy AFIS hits are made without taking 

time for examiner markup; if the initial search does not result in a hit, minutiae and possibly other features are 

marked for a standard minutiae-based search.

If the examiner determines that the latent needs to be searched against another AFIS outside the examiner’s 

immediate jurisdiction, any system that conforms to the EFS Profile Specification accepts searches using EFS 

Profile 0: Image-Only Profile or EFS Profile 2: Quick Minutiae Search Profile; alternatively (if supported by the 

interoperable AFIS), the encoding may be modified with additional features for an optional profile selected to 

maximize search accuracy against another AFIS.
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Table 1 provides a cross reference of extended friction ridge features for which EFS Profiles in which they might 

appear.

Table 1: Extended Friction Ridge Features by EFS Profile

Feature Field Mnemonic* 1 2 3 10 11 Special Cases

Region of interest 9.300 ROI X X X

Orientation 9.301 ORT X X X

Finger, palm, plantar position 9.302 FPP X X X

Pattern classification 9.307 PAT X X X

Cores 9.320 COR X X X

(no cores present) 9.325 NCOR X X X

Deltas 9.321 DEL X X X

(no deltas present) 9.326 NDEL X X X

Minutiae 9.331 MIN X X

(no minutiae present) 9.334 NMIN X X

Evidence of fraud 9.354 EOF X X

Ridge quality/confidence map 9.308 RQM X

Dots 9.340 DOT X

(no dots present) 9.346 NDOT X

Incipient ridges 9.341 INR X

(no incipient ridges present) 9.347 NINR X

Distinctive features 9.324 DIS X

Ridge flow map 9.310 RFM X

Center point of reference 9.323 CPR X

Core-delta ridge counts 9.322 CDR X

Skeletonized image 9.372 SIM X

Minutiae ridge counts 9.333 MRC X

Minutiae ridge count algorithm 9.332 MRA X

Possible lateral reversal 9.315 PLR X

Tonal reversal 9.314 TRV X

Possible growth or shrinkage 9.317 PGS X

*The term “mnemonic,” rather than “abbreviation,” is used here to maintain consistency with the base 

standard.
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4 Image-Only Searching

Image-only searches require no examiner markup. Image-only searches are conducted with an assumption that 

accuracy may be lower than for feature-based searches, but they require much less examiner time to prepare 

each search. The FBI CJIS EBTS (2011) Latent Friction Ridge Image Search transaction is an example of an imageonly search.

An image appropriate for an image-only search has no obscuring background or multiple impressions and is 

upright2(visually appears to be within approximately ±15° of upright). Large clear impressions are well suited for 

image-only searches.

 

2

This requirement stems from EFS Profile 0: Image-Only Profile having no Region of interest/ROI (field 9.300), which accommodates obscuring background 

or multiple impressions, nor Orientation/ORT (field 9.301), which accommodates non-upright or unknown orientation.
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5 Features for Fundamental Latent AFIS Searches

5.1 Region of interest/ROI (field 9.300)

The region of interest (ROI) is a rectangle or polygon that 

bounds the area of the original image containing a single 

friction ridge impression and separates it from the 

background and any other friction ridge data present in the 

image. (See figure 1.) Using an ROI is strongly recommended 

when the overall image contains multiple impressions or 

when differentiating between the friction ridge detail and 

the background is difficult.

All other features must be within the ROI, with the exception 

of the Center point of reference/CPR (field 9.323).

An ROI includes only one impression made by a single or 

contiguous portion of friction ridge skin. For example, an ROI

may be limited to a single distal fingerprint or include multiple fingers as part of a single full palm impression but 

may not include impressions of different fingers that are not connected by a common interdigital impression. 

Simultaneous impressions or other images containing multiple impressions must mark each impression 

separately. In the case of overlapping fingerprints, the ROI may 

include superimposed impressions. There can be only one ROI for 

a given image. 

A region of interest (ROI) delineates a 

single continuous friction ridge impression. 

Mark the ROI to include all of the 

impression being evaluated, while 

excluding as much as possible of the 

background and other impressions. If in 

doubt, be inclusive.

Figure 1: Region of interest.
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5.2 Orientation/ORT (field 9.301)

Orientation (ORT) indicates the distal direction towards the 

tips of the fingers. (See figure 2.) There are three options for 

indicating orientation: upright, unknown, and specific 

orientation.

1. Upright indicates that the impression is upright (“tip 

up”) within about ±15°. This is the default if not 

otherwise indicated.

2. Unknown indicates that the orientation cannot be 

determined.

3. Specific orientation indicates that the orientation can 

be determined and the impression is not upright. Specify 

the orientation. If the orientation is approximate, optional 

bounds of uncertainty may be indicated.

Although arbitrary rotation of the image is not recommended 

because of image degradation concerns, rotation of the image 

in multiples of 90° can be performed without image

degradation and is acceptable.

5.3 Finger/palm/plantar position/FPP (field 

9.302)

Indicate the area of friction ridge skin that created the print, 

using the codes from table 2 (fingers, including tips or lower 

joints), table 3 (palms), or table 4 (plantar impressions). 

If the source cannot be definitely determined, indicate any 

areas that could have been the source of the print. Note that 

there are different options when the source is unknown. If the 

physical source of the impression cannot be determined and 

may be a finger, palm, or plantar, use unknown source (18) (as 

shown in table 5); if some sources may be excluded, use one 

or more of the position codes unknown finger (0), unknown palm (20), unknown sole (60), or unknown toe (63).

These position codes are as defined in ANSI/NIST-ITL (2011), table 8, which specifies additional position codes 

that are not applicable for EFS markup, such as codes for four finger slap impressions.

The finger/palm/plantar position

indicates the portion of friction ridge 

skin that created the impression. Note 

the position only if the source area of 

friction ridge skin can be determined 

definitively or limited to a set of 

positions. 

Figure 2: Orientation marked with ±20°

uncertainty.

Orientation indicates the direction towards 

the tips of the fingers. Indicate whether the 

orientation is upright, unknown, or a 

specific orientation. 
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Figure 3: Use of rectangles to 

mark multiple finger 

segments in a latent print 

with multiple segments.

Table 2: Position Codes for Fingers 

(including Tips and Lower Joints)

Right Left

Unknown finger 0

Thumb 1 6

Index 2 7

Middle 3 8

Ring 4 9

Little 5 10

Extra digit 16 17

Table 3: Position Codes for Palms

Right Left

Unknown palm 20

Full palm 21 23

Writer’s palm 22 24

Lower palm 25 27

Upper palm 26 28

Other area of palm 29 30

Interdigital 31 34

Thenar 32 35

Hypothenar 33 36

Grasp 37 38

Carpal delta area 81 82

Full palm, including writer's palm 83 84

Table 4: Position Codes for Plantar 

Impressions

Right Left

Unknown sole 60

Sole 61 62

Unknown toe 63

Big toe 64 69

Second toe 65 70

Middle toe 66 71

Fourth toe 67 72

Little toe 68 73

Front/ball of foot 74 76

Back/heel of foot 75 77

Arch 78 79

Table 5: Position Code for Unknown Source

Unknown source (may be finger, palm, or plantar) 18

For subjects with extra fingers or thumbs, label the four fingers closest to the thumb with the 

index/middle/ring/little position codes, label the thumb closest to the fingers with the thumb position code, and 

label additional fingers with the extra finger position code for the appropriate 

hand. In the case of conjoined fingers, include the image of the entire 

conjoined finger by using the finger position closest to the thumb, and use the 

next finger position for the next fully separable finger. Use the EFS comment 

field (field 9.351) to describe specifics of the extra or conjoined fingers.

If the image/ROI contains multiple areas, label and mark each of those areas 

within the ROI with a rectangle or polygon delineating each of the areas. 

Rectangles or polygons may overlap if appropriate. If the ROI contains only a 

single area, such area markup is unnecessary. If the image includes two or 

more segments of a finger (or substantial portions of two or more segments), 

mark the image with the finger number (0-10) and mark the individual 

segments with rectangles or polygons. (See figure 3.) If the image is of a palm 

(or foot), mark each of the palm areas present with the relevant position code 

and delineate with a rectangle or polygon. (See figure 4 and figure 5.) Note that 

the interdigital and hypothenar areas overlap at the base of the little finger.
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Figure 4: Palm and finger segment positions.

Figure 5: Use of polygons to mark multiple areas within a palm impression.
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For fingerprints in which the impression does not contain the central area of the fingerprint (i.e., the core), use 

the code from table 6 to indicate the off-center position of the fingerprint image. (See figure 6 and figure 7.)

Right or left side may apply to any segment of a finger (or thumb); “tip only” applies to the distal segment.

Because only one area is present in figure 6, it is not necessary to mark the area with a polygon or rectangle.

Table 6: Off-Center Fingerprint Positions

Name Code Description

Tip T The plain or rolled extreme tip of the image

Right side R The right side of the finger or thumb

Left side L The left side of the finger or thumb

Figure 7: Off-center fingerprint 

showing extreme tip.

Figure 6: Off-center fingerprint showing left 

side of finger.
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Figure 8: Example of ambiguous 

pattern classification for a latent 

print.

Pattern classification of fingerprints

follows the Henry system. When the 

pattern classification is noted, take care 

to be inclusive of all possible pattern 

classes. 

5.4 Pattern classification/PAT (field 9.307) 

This field contains fingerprint classification information for 

the image. (See table 7.) This field does not apply to palms, 

lower joints, extreme tips, or plantar impressions. 

Classification must be conservative: if the pattern is known

precisely, indicate only a single pattern; however, if there is 

any doubt as to the precise classification, include all possible 

patterns. Figure 8 shows an example of ambiguous pattern 

classification; this latent print should have a pattern 

classification that includes BOTH right loop and double loop whorl (it is, in fact, a double loop whorl). If the

pattern cannot be classified, but a pattern type can be definitively excluded, then indicate that by including all 

possible patterns. For example, if the image contains a delta, but the image cannot otherwise be classified, then 

exclude the plain arch.

Table 7: Pattern Classification Codes

Pattern Classification General Class Subclass Whorl Delta Relationship3

Arches

Arch, type not designated AU

- Plain arch AU PA

- Tented arch AU TA

Whorls

Whorl, type not designated WU

- Plain whorl WU PW I, O, or M

- Central pocket loop WU CP I, O, or M

- Double loop WU DL I, O, or M

- Accidental whorl WU AW I, O, or M

Loops

Right slant loop RS

Left slant loop LS

Unable to print

Amputation XX

Temporarily unable to print (e.g., bandaged) UP

Unable to classify

Unable to classify UC

- Complete scar SR

- Dissociated ridges/dysplasia DR

The field consists of three information items: general class, subclass, 

and whorl delta relationship.

1. General Class indicates the basic pattern classifications 

(arches, whorls, loops).

2. Subclass indicates the subcategories of the general class, 

which applies only to arches and whorls. Indicate this information 

item only if the subclass can be determined precisely or if specific 

subclasses can be excluded. 

3. Whorl Delta Relationship may optionally be used by a human 

examiner or automated system to provide the relationship 

between the deltas in a whorl. Include this information item only 

for whorls if the subclass is known and only if the whorl delta 

 

3

I = Inner, O = Outer, M = Meeting
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Cores are marked at the focus of the 

innermost recurving ridge. Mark the 

direction of the core in the direction of 

ridge flow.

Figure 9: Placement of the 

core at the focus of the 

innermost recurving 

ridgeline, with direction in 

the direction of ridge 

flow.

Figure 10: Examples of core locations for a double loop 

whorl, plain whorl, tented arch, and central pocket loop 

whorl.

relationship can be determined precisely. Set this information item to I (Inner), O (Outer), or M (Meeting), 

following the Henry guidelines (detailed in The Science of Fingerprints (SOF), p. 60). The information item is 

Inner if the ridge emanating from the left delta passes three or more ridges above (inside) the right delta

and is Outer if the ridge emanating from the left delta passes three or more ridges below (outside) the right 

delta; otherwise, it is Meeting.

Up to seven pattern classifications may be indicated (including subclasses).

Note Complete Scar (SR) and Dissociated Ridges/Dysplasia (DR) if the fingerprint cannot be classified. If the 

fingerprint can be classified and scar(s), dissociated ridges, and/or dysplasia are present, note the 

classification(s) in this field. Note the scar(s), dissociated ridges, and/or dysplasia by using Scars and other 

distinctive features/DIS (field 9.324). Use (if desired) Core-delta ridge counts/CDR (field 9.322) to further 

subcategorize pattern classification.

5.5 Cores/COR (field 9.320)

The core or cores of a fingerprint are defined for all pattern 

classifications other than plain arches. (See table 8.) Mark (if 

desired) cores on tented arches if an innermost recurving ridge 

is present. Plain or central 

pocket loop whorls will have 

only one core if the innermost 

recurving ridge is circular or two 

cores if elliptical. A whorl with 

only one core does not have a 

defined direction. For plain arches, a Center point of reference/CPR (field 9.323) 

may be marked instead of marking a core.

For palmprints, lower 

joints, or plantar 

impressions, define 

core-like patterns by

using this field if such 

structures are present. 

The location of a core is 

at the focus of the 

innermost recurving ridge: if the curve of the 

innermost continuous ridge is viewed as a section of a 

circle, the core is the center of that circle. Note that in 

EFS, the location of cores differs from that defined in 

SOF to accommodate AFIS interoperability. Figure 9

and figure 10 show examples of core locations. Use (if 

desired) an optional radius of uncertainty if the 

location is not known precisely. If the location cannot 

be determined because of poor clarity or ambiguity of 

the innermost recurving ridge, size the radius of 

uncertainty to include other possible locations of the 

core.

The direction of the core is the direction of ridge flow. 
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Deltas are marked where the three 

directions of flow converge, with 

directions marked in each of the three 

directions of flow. 

Figure 11: Examples of delta 

markup, with radii of uncertainty 

indicated when the delta 

structure is ambiguous. Figure 12: Palm with carpal delta 

and inter-digital deltas.

If the core’s direction cannot be accurately determined, a range of direction uncertainty may be indicated

optionally.

In the special case that the core cannot be seen in the impression but a reasonable estimate of location can be 

made, it is permissible to mark the core in the approximate location with an appropriately large radius of 

uncertainty. 

Table 8: Maximum Number of Cores and Deltas by Fingerprint Pattern Classification

Pattern Classification Cores Deltas

Arches - Plain arch 0 0

- Tented arch 0 or 1 0 or 1

Whorls

- Plain whorl 1 or 2 2

- Central pocket loop 1 or 2 2

- Double loop 2 2

- Accidental whorl Any number Any number

Loops 1 1

If analysis determines that there are no cores present, that is to be indicated by using No cores present/NCOR 

(field 9.325).

5.6 Deltas/DEL (field 9.321)

The delta or deltas of a fingerprint are defined for loops and 

whorls. Tented arches may optionally have deltas marked if 

such a structure is present. Accidental whorls may have any 

number of deltas. Mark interdigital and carpal deltas for palms, 

and mark (if desired) delta-like patterns for other areas of 

friction ridge skin.

The location of the delta 

is at the center of the delta structure, where the three directions of flow

converge. Use an optional radius of uncertainty if the location cannot be 

determined precisely because of poor clarity or ambiguity of the delta 

structure. (See figure 11.)

Mark the three directions of the 

delta in the three directions of 

ridge flow. When orientation is 

known, mark the direction closest 

to upright first, proceeding 

counter-clockwise. If the 

directions cannot be determined

accurately, define a range of 

direction uncertainty for each 

direction. (See figure 12.)

In the special case that the delta 

cannot be seen in the impression 

but a reasonable estimate of 

location can be made, mark the 

delta in the approximate location

(if desired), with an appropriately large radius of uncertainty. 
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Bifurcations are marked at the “Y” of the 

ridge, with the direction (“theta”) running 

down the valley between the fork of the 

bifurcation.

Ridge endings or minutiae of unknown 

type are marked at the “Y” of the valley, 

with the direction running up the ridge.

Figure 13: Minutia placement for a bifurcation.

Indicate the type of delta when known, as defined in table 9.

If one or more deltas are present and the feature set is from a fingerprint, Pattern classification/PAT (field 9.307)

should be defined. This does not mean that the classification has to be known definitively, but must at least be 

known to the extent of excluding plain arches.

If analysis determines that there are no deltas present, that is to be indicated by using No deltas present/NDEL

(field 9.326).

Table 9: Delta Type

Code Applies to Name Description

L Finger Left fingerprint delta The delta to the left of the image for whorls or right 

loops—for accidental whorls with more than two deltas, 

this indicates the leftmost delta.

R Finger Right fingerprint delta The delta to the right of the image for whorls or left 

loops—for accidental whorls with more than two deltas, 

this indicates the rightmost delta.

I00

I02..I05

I07..I10

Palm Interdigital delta (with finger 

number)

The deltas at the base of the fingers in the interdigital 

areas—note the finger number if known; otherwise, set

the number to “00”. Thumbs do not have interdigital 

deltas. Figure 12 shows examples of I07 through I10.

C Palm Carpal delta The delta at the base of the palm where the thenar and 

hypothenar meet. Figure 12 shows an example.

<empty> Finger, palm, or foot Other delta Any other delta or delta-like structure in a friction ridge 

impression.

5.7 Minutiae/MIN (field 9.331)

Mark the type of minutiae if clearly identifiable as a bifurcation or ridge ending; otherwise, mark the type as 

unknown. The locations for bifurcations and ridge endings 

are equivalent: the placement of a bifurcation at the “Y” of 

the ridge with the theta angle running down the valley (see 

figure 13) is determined the same as for a ridge ending at the 

“Y” of the valley with the theta angle running up the ridge

(see figure 15); there would be no difference in location if 

the image were tonally reversed (black for white). The ridge 

ending location corresponds with that used for the FBI’s 

Integrated Automated Fingerprint Identification System

(IAFIS) and Next Generation Identification (NGI), as well as 

the INCITS 378, (ANSI/INCITS 2004) definition, but 

differs from some legacy vendor-specific 

approaches. 

Mark all minutiae in the impression, not omitting 

short ridges or minutiae near cores and deltas. If a 

receiving AFIS does not use such minutiae, it is 
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Figure 15: Minutia 

placement for a ridge 

ending.

Figure 14: Minutia placement when type is 

unknown.

incumbent on that system to ignore them. See Dots/DOT (field 9.340) and incipient ridges/INR (field 9.341) for 

instructions on how and when to mark dots.

The angle of a minutia may be more difficult than usual to determine when the

direction of ridge flow is ambiguous, when the ridges are near the minutiae curve,

or when the ridges come together at obtuse angles. In such cases, the angle of a 

bifurcation is determined by following each of the three ridges forming the 

bifurcation for a distance of about three ridge widths (1.93mm or 0.064”); the 

smallest of the three angles formed by the rays is bisected to indicate the minutiae 

direction. The angle of a ridge ending is determined equivalently, based on following 

the three valleys that form the ridge ending.

If the precise location for a ridge 

ending cannot be determined, 

mark a radius of uncertainty to 

include the area of possible locations. (See figure 14.) If the 

type is unknown, indicate the radius of uncertainty.

Because of the frequency with which minutiae appear to be 

ridge endings in one impression and bifurcation in another, 

even in clear images, it is recommended that the minutiae 

type be used as supporting evidence rather than as a basis 

for exclusion. Mark all complex minutiae types as 

combinations of bifurcation/endings; for example, mark a 

crossover or trifurcation as two bifurcations located closely together. 

In many cases, distinguishing among dots, incipients, and ridge edge protrusions is a judgment call. There are

two unusual minutiae shown in figure 16: a crossover (at left of the right image, marked in green as a distinctive 

feature) and a delta-shape minutia (near the core, marked in red with direction uncertainty range).

Figure 16: Example of original image and markup of dots (shown in blue) and incipients (shown with 

blue lines).

If analysis determines that there are no minutiae present, that is to be indicated by using No minutiae 

present/NMIN (field 9.334).
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5.8 Evidence of fraud/EOF (field 9.354)

An examiner should always indicate whenever there is 

evidence that the image may be fraudulent, regardless of the 

EFS profile used. A comment must be included to explain what 

indications of fraud are present. There are four types of fraud: 

evasion, spoofing, forged evidence, and fabricated evidence.

1. Evasion includes actions that prevent/lessen the 

likelihood of matching, such as by degrading or 

obscuring physical characteristics or mutilating 

fingers. Examples are acid balding of fingers or use of 

a knife or laser to alter the fingerprints.

2. Spoofing includes purposefully attempting to be identified as a different person in a biometric system by 

modifying biological characteristics or using fabricated characteristics. Examples are using a rubber 

finger, gelatin fingerprint attached to a real finger, or image of a fingerprint to fool a biometric reader.

3. Forged evidence is forensic evidence that was fraudulently placed on the surface from which it was 

collected, using another mechanism or device than the natural contact with friction ridge skin. An 

example is using a rubber lifter to move a fingerprint from its actual source to another source.

4. Fabricated evidence is forensic evidence that never existed on the surface from which it was supposedly 

collected. An example is a crime scene examiner deceitfully mislabeling the source of images or lift 

cards.

Note evidence of fraud if there is any 

indication that the image may be 

fraudulent. The types of fraud include

evasion, spoofing, forged evidence, and 

fabricated evidence.
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The ridge quality/confidence map is a 

standard color-coded means of

indicating the clarity of the print. This is 

the means by which the recipient can 

determine whether the features 

marked at a given location are 

definitive or debatable.

6 Additional features used in latent AFIS searches

6.1 Ridge quality/confidence map/RQM (field 9.308)

Local friction ridge quality is an assessment of the clarity of 

each area within an image. The colors and categories are 

defined in figure 17. Because accurate and consistent markup 

of ridge quality is essential, follow the guidelines in this 

section as closely as possible. 

Ridge quality can be generated by an automated process with 

human reviewed/editing, or it can be painted manually by a 

human examiner.

While automated systems and all examiners should ideally 

concur on ridge quality markup, in practice individual 

examiners are likely to disagree at times. An individual 

examiner may differ and create a different quality assessment 

that documents what that specific examiner sees in the print.
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Is any ridge information present?

Local area in Friction Ridge Image

No Background

Are you certain of the continuity of ridge flow?

Yes No Debatable ridge flow

Are you certain of the location, presence, and absence of all minutiae?

Yes Definitive ridge flow, debatable minutiae No

Are the ridge edge contours clear and unambiguous? Yes Definitive minutiae, debatable ridge edge No

Yes All data is clear

Are you certain of the presence, direction and continuity of the ridges in the area? Are you certain that the ridges entering, passing through, and exiting the area are the same ridges and not due to another impression, double tap, or a smear?

Are you certain of the presence or absence of all minutiae in the area – to the extent that contradiction in a comparison would be reason for an exclusion?

Are the edges of all ridges in the area clear and continuous?

Are the pores clear and unambiguous? Definitive ridge edge, debatable pores No Yes Are you certain that all pores in the area can be located precisely?

Are any areas outside the ROI marked as background?

Figure 17: Decision process for local friction ridge quality.
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Figure 18 shows examples of ridge quality markup. In a graphical interface in which the quality map is 

superimposed on the image, these colors are displayed as a semitransparent layer on the image. The images of 

ridge quality markup allow an examiner (or software program) reviewing the image a straightforward means of 

assessing the value and data content of the image: large Blue areas are excellent, Green areas are satisfactory, 

Yellow areas may potentially contain false or missed features, and Red areas are not of value. Automated tools 

that calculate overall and corresponding quality assessments that are based on the size and continuity of these 

areas are being developed.

Figure 18: Ridge quality markup on latent and exemplar prints.
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The ridge quality map is used to define the confidence in all other features. (See table 9.) In addition, when the 

quality map indicates a high-quality region in which features are not marked (such as an open field of ridges), 

that information can be used as “negative features” or definitive absence of features, which may be used as 

support for exclusion.

Table 9: Ridge Quality Map Values and Their Relation to Feature Confidence Ridge flow Minutiae Dots Incipients Ridge edge features

Pores

Black 0 Background 

Red 1 Debatable ridge flow  

Yellow 2

Definitive ridge flow, 

debatable minutiae   

Green 3

Definitive minutiae, 

debatable ridge edges   

Blue 4

Definitive ridge edges, 

debatable pores  

Aqua 5 All features definitive 

 Definitive and 

unambiguous

Presence, absence, and location are definitive.

Contradictory presence or absence of definitive features 

in a comparison is cause for exclusion.

 Debatable or 

ambiguous

Features may be marked, but presence, absence, and 

location are debatable. Corresponding/contradictory 

features in a comparison are supporting evidence for 

individualization/exclusion.

 Not discernible or 

unreliable

Features should not be marked and are ignored if 

present. No evidence for individualization or exclusion in 

a comparison exists.

Note particularly two critical distinctions:

If the presence or absence of minutiae is definitive enough to be used for exclusion in future comparisons, 

mark the area Green or better; otherwise, mark the area Yellow.

If the area was left as a single impression with continuity of ridge flow, mark the area Yellow or better; 

however, if a double tap, movement, or second impression resulted in discontinuous ridge flow, mark the 

separation between continuous areas with a region of Red.

The following sections provide examples and more detailed explanations of the levels of ridge quality. In each 

case, if there is doubt as to which level of ridge quality to assign, use the lower quality.

6.1.1 Black —Background

Background areas are any areas of the image that are not from the impression of interest. Any of the image 

outside of the ROI is by definition considered background, including extraneous impressions. When displayed by 

workstation software or in color-coded images, Black areas may be shown by lack of color, rather than Black per 

se. (See figure 18.)
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Figure 19: Examples of Red areas—debatable 

ridge flow.

6.1.2 Red —Debatable ridge flow

Red areas are those portions of images for which there is 

some (minimal) ridge information but for which the 

examiner (or software) has low or no confidence that the 

ridges in the area are continuous. Indicate those areas of the 

image that contain ridge data but that are of insufficient 

quality to use in comparison. These areas are of greatest 

importance for images with discontinuities, as discussed in 

the next section. (See figure 19.)

6.1.3 Yellow —Definitive ridge flow, debatable 

minutiae

Yellow areas are those portions of images for which the examiner (or software) has confidence in the presence 

and direction of ridge flow, but the location and/or presence of minutiae are debatable. 

Mark an area Yellow, instead of Green, to indicate that marked minutiae are low confidence and that areas 

without marked minutiae may have undetected minutiae. 

Mark an area Yellow instead of Red, to indicate certainty that the area is from a continuous impression. 

Superimposed ridge detail from two impressions can be marked Yellow only if there is no doubt about the 

continuity of the ridge detail for the impression of interest. (See fFigure 20.)

Figure 20: Examples of Yellow areas—definitive ridge flow with debatable minutiae.
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Figure 22: Examples of images with Blue quality—definitive ridge edges with 

debatable pores.

6.1.4 Green—Definitive minutiae

Green areas are those portions of images in which there is no doubt that any and all minutiae can be accurately 

detected, but without clear ridge edges. By assessing an area as Green or better, the examiner (or software) is 

indicating that the likelihood of false or missed minutiae in the area is remote. Minutiae in Green areas may 

require limited interpretation. (See Figure 21.)

6.1.5 Blue —Definitive ridge 

edges, debatable pores

In Blue areas, all levels of ridge 

features other than the pores are 

not only visible or interpretable 

but obvious and unambiguous, 

including the shape and contours 

of ridge edges, and the shape and 

precise location of all minutiae, 

dots, and incipients. Pores may be 

Figure 21: Examples of Green areas—definitive minutiae.
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Figure 23: Example of print 

with Aqua quality—All 

features definitive.

absent or debatable. Blue areas are common in well-captured exemplars, but much less frequent in latents. (See 

Figure 22; portions of the leftmost image are Aqua quality.)

6.1.6 Aqua —All features (ridge edges, minutiae, ridge flow, and 

pores) definitive

In the highest-quality areas, all levels of ridge features are not just visible or 

interpretable but obvious and unambiguous, including the shape and 

contours of ridge edges and the shape and precise location of all minutiae, 

dots, incipients, and pores. Mark Aqua only in the specific areas in which the 

pores are obvious and unambiguous. (See Figure 23.)

6.1.7 Continuity of ridge flow

Careful marking of ridge quality is most important for images with extensive 

discontinuities. In an image, such as the one shown in figure 24, limit the 

analysis of the image to the contiguous areas of Yellow or better. The small 

separations of Red are critical because those define the problem areas that

can cast doubt on comparison decisions. The image contains at least five

impressions; impressions other than the one of interest are outside the ROI 

and, therefore, are considered background. If the multiple prints in this image need to be searched, mark and 

search each impression separately.

If there is any doubt that two portions of the image are not from a single impression (such as a double tap, 

smear, or second impression), separate those areas by Red areas.

For minor occlusions, such as printed text or lines, mark (if desired) the area Yellow if the occlusions are thin 

enough that it is clear which ridges on one side connect to specific ridges on the other side.

Figure 24: Latent image with multiple discontinuous areas.
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6.2 Dots/DOT (field 9.340) and incipient ridges/INR (field 9.341)

A dot is an isolated single ridge unit (ridge that contains a single pore). Generally, the width of a dot is similar to 

the width of neighboring ridges, and the length of a dot 

approximates its width.

An incipient ridge is a thin ridge, substantially thinner than 

local ridge width. Incipient ridges generally do not contain 

pores. Incipients frequently appear as a series of separate 

segments.

Often the distinction between a dot, an incipient ridge, and 

a short ridge is unclear. 

If the feature is similar in width to the local ridge width 

and at least twice as long as it is wide, mark it as a 

standard ridge with a pair of ridge endings. If pores are 

visible, a standard ridge should have at least two pores.

If the feature is similar in width to the local ridge width,

but about as long as it is wide, mark it as a dot. 

If the feature is substantially thinner than local ridge 

width, mark it as an incipient ridge.

Mark a dot at its center point. Mark an incipient ridge with a line segment along its longest dimension. If an 

incipient ridge is composed of a series of segments, do the following:

Mark the series as a single line if the segments of the incipient are close together or the separations 

between segments are indistinct.

Mark the series as separate incipient ridges if the segments are clearly separate (with distinct lines drawn 

for each). 

If an unbroken incipient ridge curves, mark it as a series of adjoining line segments. In many cases, distinguishing 

among dots, incipients, and ridge edge protrusions (spurs) is a judgment call. (See figure 16.)

If analysis determines that there are no dots present, indicate that by using No dots present/NDOT (field 9.346).

If analysis determines that there are no incipient ridges present, that is to be indicated by using No incipient 

ridges present/NINR (field 9.347).

6.3 Scars and other distinctive features/DIS

(field 9.324)

Mark scars, dysplasia/dissociated ridges, warts, blisters, or 

other abnormalities that interfere with normal ridge flow as 

distinctive features. These features are physical aspects of 

the friction skin itself, not issues specific to the impression

(such as smudging). Minor cuts (white lines) that do not 

affect ridge flow are not considered scars. (See figure 25.)

A dot is a very short ridge whose length 

approximates its width. A dot is marked at its 

center point.

An incipient is a thin ridge, substantially 

thinner than local ridge width. An incipient is 

marked with a line segment along its longest 

dimension. 

If the distinction between a series of dots and 

an incipient ridge is unclear, it may be

marked as one or the other. 

Scars or other physical abnormalities that 

interfere with normal ridge flow are

marked as distinctive features.
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Figure 25: Distinctive features: dissociated ridges, scar, scar.

Enclose the relevant area with a polygon, with the appropriate code from table 10.

When recording the presence of unusual features in this field, mark as part of casework annotation.

Table 10: Types of Distinctive Features

Code Description

Physical 

abnormalities —

must be marked

SCAR Scar

WART Wart or blister

DYSPLASIA Dissociated ridges/dysplasia

Unusual features

— may be 

marked

optionally for 

casework 

annotation

MINGROUP Unusual group or cluster of minutiae

CORE Unusually distinctive core area

DELTA Unusually distinctive delta area

MINUTIA Unusually shaped minutia

CREASE Unusually distinctive crease

CLEAR Large clear field of ridges; large clear area with no 

minutiae

OTHERFEAT Other unusual features not characterized elsewhere; 

details should be noted in comments

6.4 Ridge flow map/RFM (field 9.310)

Ridge flow refers to the directional arrangement of friction 

ridges and is most often used for pattern-level screening of 

fingerprints. Ridge flow provides more specific detail than 

pattern classification and can be used more effectively on 

partial fingerprints. It can be used by AFIS algorithms as an

end matcher to refine the candidate list produced by the 

feature matchers.

The ridge flow map contains the direction 

of the ridges at various sampling points.
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For fingerprints, the center point of 

reference is the center of the distal pad 

of the finger.

For tips or lower joints, the lateral 

center (centerline of the finger) should

be marked.

Figure 26: Ridge flow map.

Ridge flow map markup, as shown in figure 26, is typically started using automated tools to extract the flow 

directions from the image. This automated markup is then corrected by the examiner (if necessary) to correct 

inaccuracies in the automated flow map. A latent corresponding to the right half of this print would appear to be 

a left slant loop; ridge flow maps permit rapid automatic comparison of such partial prints, unlike traditional 

pattern classification.

6.5 Center point of reference/CPR (field 9.323)

This field contains the location of a center point of reference of 

a fingerprint, which is used to define how centered a 

fingerprint is, as a feature, for registration or orientation, and 

for quality measurements. Although the core may serve some 

of the same purposes, a center point of reference is defined for 

arches and provides a single center location for complex 

whorls, unlike cores. The center point of reference does not 

apply to palmprints.

The center point of reference is the sole EFS feature that can be 

located outside of the ROI; as such, this allows the estimated 

center of the finger to be marked even for an extreme side or 

tip. The center point of reference must be within the bounds of 

the overall image itself. 

The location of a center point of reference can be determined using different approaches. Use the uppermost 

point of the ridge with greatest curvature approach when practical; otherwise, use an estimate of the 

approximate center of the distal fingerprint pad, with a radius of uncertainty. For extreme tips, lower joints, or 

any cases where the center of the distal fingerprint pad cannot be estimated, indicate the lateral centerline of 

the finger. The workstation software provides a means to indicate which method to use.
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Figure 29: Lateral center 

example.

Uppermost point of the ridge with greatest curvature

To precisely determine the center point of reference, use the 

uppermost point of the ridge with greatest curvature. For a 

fingerprint with a known or estimated orientation, determine 

the center point by finding the highest point of each ridge that 

is convex and pointing upward and measuring the 

curvature/peak angle by following the ridge 1.63mm (0.064in, 

about 3 ridge widths) in both directions from that point. The 

point with the minimum angle4(greatest curvature) is the 

center point of reference. (See figure 27.)

Estimate of the approximate center of the distal fingerprint pad

In this approach, estimate the center of the distal pad of the 

finger by measuring halfway vertically between the distal 

interphalangeal crease and the tip, and halfway horizontally 

across the finger. (See figure 28.) This is the center of the 

physical finger, not the center of the print as seen in the image.

Figure 28: Examples of center point of reference based on an estimate of the approximate center of 

the finger.

Lateral centerline of the finger

For arches, tips, and lower joints, if the approximate 

centerline of the finger can be determined, mark the lateral

(horizontal) center. The location is not meaningful in the 

other direction (longitudinally or along the finger). Lateral 

center is only meaningful if the orientation is known or can 

be estimated; the point marked is the center with respect 

to the orientation angle. (See figure 29.)

 

4

This angle need not be an integer value.

Figure 27: Uppermost point of the 

ridge with greatest curvature—

measurements are angles, in 

degrees.
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6.6 Core-delta ridge counts/CDR (field 9.322)

This field contains the count of intervening ridges between each 

core and delta. Each ridge count can be set as an exact value, or 

minimum and maximum values can be specified. If the exact 

value is known, then that value should be put in both the 

minimum and maximum fields. (See figure 30. For details on 

ridge counting, see 6.8, Minutiae ridge counts/MRC (field 9.333)

and Minutiae ridge count algorithm/MRA (field 9.332).)

Figure 30: Core/delta ridge count example.

6.7 Skeletonized image/SIM (field 9.372)

The skeleton, also known as a ridge tracing, is a representation of the ridge structure of the print in which the 

thinned skeleton follows the midpoint of each ridge. Incipient 

ridges, dots, ridge discontinuities, and protrusions are not 

included in the skeleton. (See figure 31.)

When the skeleton is marked, use automated tools to extract 

an approximation of the skeleton to use as a starting point, 

or create the skeleton in its entirety. Then edit the skeleton 

to correct extractor errors and verify that the skeleton is 

consistent with minutiae markup and consistent with quality 

markup (if present).

When a skeleton is used in combination with the ridge 

quality map, mark the skeleton as follows with respect to 

the ridge quality map: 

o In all areas marked “definitive minutiae” (Green) or better, the skeleton must be complete and 

unbroken, and the skeleton’s ridges stop only at ridge endings. 

For loops and whorls, note a count of 

intervening ridges between each core and 

delta. If the exact count cannot be 

determined, define a range or minimum.

The skeleton is a thinned representation of 

the ridge structure of the print. 

Skeletons may be used optionally when 

searching some AFIS systems to increase 

accuracy, at the cost of additional 

examiner markup time.
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o In areas marked “debatable minutiae” (Yellow), the skeleton may be incomplete, and the skeleton’s 

ridges may stop at locations that do not correspond to ridge endings.

o Any areas of the print that 

cannot be represented in the 

skeleton must be marked 

“debatable minutiae” (Yellow) or 

worse.

When a skeleton is used and the ridge 

quality map is not present, treat the 

skeleton as if the entire region of 

interest had been marked using the 

ridge quality map value of “debatable 

minutiae” (Yellow). The skeleton may 

be incomplete, and the skeleton’s 

ridges may stop at locations that do 

not correspond to ridge endings.

Skeletons are of value in AFIS matching 

because each ridge segment within the 

skeleton can be used to show the 

relationships of the minutiae and other 

features connected by that ridge, enabling 

a topological representation of the print.

6.8 Minutiae ridge counts/MRC (field 9.333) and Minutiae ridge count algorithm/MRA 

(field 9.332)

The ridge count is the number of ridges crossed or touched on a straight line between the minutia and each of 

its neighbors. The count begins at zero at the minutia and increases by one for each ridge crossed, not including 

the ridges that form either of the endpoint minutiae. For example, if one of the minutiae is a bifurcation and if 

the straight line passes through one of the ridge segments forming the bifurcation, the latter is not counted.

(See Figure 32.)

Two algorithms calculate which neighbors should have ridge 

counts calculated, based on four or eight neighbors per minutia.

(See ANSI/NIST-ITL (2011), table 44.) Set Minutiae ridge 

counts/MRC (field 9.333) and Minutiae ridge count 

algorithm/MRA (field 9.332) accordingly.

Because of the curving of ridges, the straight line between a 

minutia and its neighbor might cross a ridge twice (or more). Do 

not count the additional crossing unless the straight line first 

passes through at least the center of an adjacent valley. Do not 

count a ridge unless the straight line passes at least to the center 

of the ridge. 

Specify the ridge count as unknown when it is not possible to estimate or determine the ridge count within plusor-minus one ridge.

Figure 31: Skeleton marking.

Ridge counts indicate the intervening 

number of ridges between minutiae.

Use ridge counts optionally when 

searching some AFIS systems to 

increase accuracy, at the cost of 

additional examiner markup time.
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In addition, EFS ridge counts5do not have an upper bound.

Figure 32: Minutiae ridge counts—The count of intervening ridges in this case is 7 and does not include the ridges that 

form either of the endpoint minutiae.

 

5

EFS ridge counts differ from ridge counts used by IAFIS, which limits ridge counts to 13, in that the count is of the intervening ridges, not the intervening 

number + 1. NGI does not use ridge counts.
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7 Features used in special cases

7.1 Possible lateral reversal/PLR (field 9.315)

-

7.2 Tonal reversal/TRV (field 9.314)

Ridges in friction ridge images are generally represented as dark areas 

with valleys as light areas. This field indicates whether all or part of the 

image is reversed tonally (black for white). Options include Negative 

(ridges are light and valleys are dark throughout the image) or Partial 

(ridges are light and valleys are dark only in portions of the image). (See 

ANSI/NIST-ITL (2011), table 36.) Tonal inversion can occur for reasons,

such as processing method, imaging method, or heavy pressure. 

When this field is set, the image in the transaction is saved as it was originally received (i.e., tonally reversed): 

setting this field and reversing the image when saving results in inconsistent data. When this field is set, a 

software user interface may display the tonally corrected image but save the image as originally received with 

this field set.

7.3 Possible growth or shrinkage/PGS (field 9.317)

In the unusual circumstance that the friction ridge impression is believed 

to have changed size or scale from potential comparisons, such as for 

deceased subjects with swollen or desiccated skin or for comparison of

adult and juvenile prints, indicate such a change in Possible growth or 

shrinkage/PGS (field 9.317). In these cases, the size of ridges and 

distances between ridges change to a greater extent than would 

ordinarily be assumed in comparisons; this field acts as a flag to indicate 

that greater than ordinary dimensional variation should be expected in 

Tonal reversal indicates if all or 

part of the image is reversed 

tonally (black for white).

Possible growth or shrinkage

indicates that the print may

have changed size or scale 

because of growth, swelling, or 

desiccation.

Possible lateral reversal 

indicates if the impression is or 

may be flipped left for right.
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performing subsequent comparisons. Options include Growth (impression is believed to be dimensionally larger 

than exemplars or other prints from the same subject), Shrinkage (impression is believed to be dimensionally 

smaller than exemplars or other prints from the same subject), or Both (may be either Growth or Shrinkage).

(See ANSI/NIST-ITL (2011), table 38.)
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8 Terminology

Bifurcation The point at which one friction ridge divides into two friction ridges

Core-delta ridge counts A count of intervening ridges between a core and a delta, applies only to 

loops and whorls

Creases and linear discontinuities Major creases, or permanent flexion creases: the named creases that 

separate the joints of the fingers and divide the palm

Minor creases, or cracks, cuts, and thin or nonpermanent scars: collectively 

called linear discontinuities

Distal segment The segment of a finger or thumb farthest from the palm

Distinctive characteristic An area containing unusually discriminating/unique characteristics that 

cannot be defined adequately using the other features, such as scars

Dot A single ridge unit

Exemplar An impression or image of friction ridge skin purposely collected with the 

knowledge of the subject, a non-latent friction ridge image

Finger/palm/plantar position The portion of friction ridge skin that created the impression

Friction ridge skin The skin found on the palms of the hands and soles of the feet

Incipient ridge A friction ridge not fully developed that appears shorter and thinner in 

appearance than fully developed friction ridges

Lateral center The center line of a finger (if it can be determined) for arches, tips, and 

lower joints

Local quality issues One or more areas containing localized quality or transfer issues that 

indicate that the anatomical friction ridge features may not have been 

accurately represented in the image

Medial segment The middle segment of a finger, not present in thumbs

Minutiae Features marked on a latent print, generally used to refer to bifurcations 

and ridge endings

Minutiae ridge counts The intervening number of ridges between minutiae

Orientation The distal direction, towards the tips of the fingers

Pattern classification The general shape or pattern of the impression

Plantar The friction ridge skin on the feet (soles and toes)

Pores Small openings in the friction ridge allowing for secretion of sweat

Profile (EFS Profile) Sets of EFS features to be used in latent friction ridge (fingerprint, 

palmprint, or plantar) searches of AFIS systems from different vendors;

different EFS Profiles allow for tradeoffs between examiner time and search 

accuracy

Protrusion An abrupt increase in ridge width that is not long enough to be called a 

bifurcation (also known as a spur)

Proximal segment The segment of the finger or thumb closest to the palm

Region of interest (ROI) A single continuous friction ridge impression
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Ridge edge features Protrusions and indentations at the edges of ridges

Ridge ending The termination point of a single, continuous ridge

Ridge flow The arrangement and direction of adjacent friction ridges.

Ridge flow map A representation of the direction of ridge flow at sampling points in a grid 

superimposed over a friction ridge image

Ridge quality A means by which a user may determine whether all features are definitive 

or debatable

Ridge path The path of a single ridge

Ridge segment A section of a ridge that connects two minutiae so each ridge segment starts 

and stops either where the ridge intersects another ridge path segment (a 

bifurcation), ends (a ridge ending), or leaves the region of interest (also 

known as ridge path segment)

Skeleton A thinned representation of the ridge structure of a friction skin image in 

which all pixels are white except for a thinned black skeleton following the 

midpoint of each ridge (also known as a ridge tracing or skeletonized image)
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9 References

ANSI/INCITS (American National Standards Institute/InterNational Committee for Information Technology 

Standards). 2004. INCITS 378-2004, Finger Minutiae Format for Data Interchange. 

http://webstore.ansi.org/RecordDetail.aspx?sku=ANSI+INCITS+378-2004.

ANSI/NIST-ITL (American National Standards Institute/National Institute of Standards and Technology, 

Information Technology Laboratory). 2011. American National Standards Institute/National Institute of 

Standards and Technology, Information Technology Laboratory: Data Format for the Interchange of 

Fingerprint, Facial & Other Biometric Information, 1-2011, NIST Special Publication 500-290.

http://biometrics.nist.gov/cs_links/standard/AN_ANSI_1-2011_standard.pdf.

Department of Defense. 2011. Department of Defense Electronic Biometric Transmission Specification. 

Version 3.0, DIN: BIMA-STB-STD-11-001.

http://www.biometrics.dod.mil/Files/Documents/Standards/DoD_EBTS_v3_0.pdf.

FBI CJIS (Federal Bureau of Investigation Criminal Justice Information Services Electronic). 2011. Electronic 

Biometric Transmission Specification, IAFIS-DOC-01078-9.3.

https://www.fbibiospecs.org/docs/EBTS_v9_3_Final%2012_07_11_clean.pdf.

Federal Bureau of Investigation 1984. The Science of Fingerprints; Rev 12-84. Washington, DC: Federal 

Bureau of Investigation.

ICPO/INTERPOL AFIS (International Criminal Police Organization-International Police Automated Fingerprint 

Identification System Expert Group). 2011. Data Format for the Interchange of Fingerprint, Facial & SMT 

Information: INTERPOL Implementation, 1-2007, Version No. 5.03, May 24, 2011. 

https://www.interpol.int/Public/Forensic/fingerprints/RefDoc/ImplementationV5.pdf.

NIST-OLES (National Institute of Standards and Technology, Law Enforcement Standards Office). 2012. 

Extended Feature Set Profile Specification. http://www.nist.gov/itl/iad/ig/ansi_standard.cfm. 

NIST-OLES (National Institute of Standards and Technology, Law Enforcement Standards Office). 2013. 

Latent Interoperability Transmission Specification. http://www.nist.gov/itl/iad/ig/ansi_standard.cfm.

Prüm. 2008. Draft Council Decision on the Implementation of Decision 2008/.../JHA on the stepping up of 

cross-border cooperation, particularly in combating terrorism and cross-border crime. 

http://register.consilium.europa.eu/pdf/en/08/st09/st09152-ad01.en08.pdf.
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10 Acknowledgments

This document builds upon ANSI/NIST-ITL (2011); therefore text, tables, and figures (see table 11) are borrowed 

heavily from that document, as well as from the EFS Profile Specification. 

Table 11: Tables and Figures Reproduced from ANSI/NIST-ITL (2011)

Markup Instructions ANSI/NIST-ITL

Figure 2 Figure 28

Figure 4 Figure 3

Figure 5 Figure 30

Table 6 Table 31

Figure 6 Figure 31

Figure 7 Figure 31

Table 7 Table 32

table 8 Table 39

Figure 9 Figure 8

figure 10 Figure 9

figure 12 Figure 32

Table 9 Adapted from Table 40

figure 13 Figure 36

figure 15 Figure 37

figure Figure 38

figure 17 Figure 27

table 9 Adapted from Table 103

table 10 Table 42

figure 27 Figure 34

The FBI’s Universal Latent Workstation, a reference implementation of EFS, was used to create examples for this 

document, and text in the discussion of ridge counts is derived from its help documentation. The ridge quality

map definitions used in EFS were derived from research conducted by the FBI Laboratory and Noblis.
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The editors of this document are:

Melissa Taylor

Law Enforcement Standards Office

Office of Special Programs

Will Chapman

Austin Hicklin

George Kiebuzinski

John Mayer-Splain

Rachel Wallner

Noblis

Falls Church, VA

Peter Komarinski

Komarinski & Associates, LLC

Rotterdam, NY

Ellie Abrams

ESA Editorial and Training Services, Inc.

Burke, VA