Mobile ID Device

Best Practice Recommendation

Version 2.1

NIST Special Publication 500-280v2.1 500-280 Version 2(2015)

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Mobile ID Device BPR Version 2.1

NIST Special Publication 500-280v2.1

Mobile ID Device 

Best Practice Recommendation

Version 2.1

Kevin Mangold

Information Access Division

Information Technology Laboratory

This publication is available free of charge from:

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September 2016

U.S. Department of Commerce

Penny Pritzker, Secretary

National Institute of Standards and Technology

Willie May, Under Secretary of Commerce for Standards and Technology and Director
Mobile ID Device BPR Version 2.1

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 500-280v2.1 

Natl. Inst. Stand. Technol. Tech. SP 580-280v2.1, 60 pages (September 2016)

CODEN: NSPUE2

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TABLE OF CONTENTS

Table of Contents

1 Introduction ............................................................................................................................................... 1

2 Scope............................................................................................................................................................. 1

3 Taxonomy and Definitions ..................................................................................................................... 3

4 System Design Considerations .............................................................................................................. 5

5 Data Format............................................................................................................................................. 10

6 Data Quality............................................................................................................................................. 10

7 Friction Ridges........................................................................................................................................ 12

7.1 Friction Ridge Capture Devices.......................................................................................................... 12

7.1.1 Friction Ridge Acquisition Profiles .............................................................................................. 15

7.1.1.1 Flat Images and Rolled Images................................................................................................ 16

7.1.1.2 Gray Levels.................................................................................................................................... 16

7.1.1.3 Acceptable Image Resolution .................................................................................................. 17

7.1.1.4 Image Dimension ........................................................................................................................ 17

7.1.1.5 Compression Algorithm ............................................................................................................ 17

7.1.1.6 Compression Ratio ..................................................................................................................... 18

7.1.1.7 Simultaneous Fingers ................................................................................................................ 18

7.1.1.8 Sensor Certification.................................................................................................................... 18

7.2 Fingerprint Capture Unit Equipment Specifications.................................................................... 20

7.3 Fingerprint Capture of Exemplars from Persons.......................................................................... 21

7.3.1 Capturing Fingerprints from Living Persons........................................................................... 21

7.3.2 Capturing Fingerprints from Deceased Persons .................................................................... 22

7.4 Capture of Latent Fingerprints from Objects ................................................................................. 23

7.5 Palm Print Capture Unit Equipment Specifications ..................................................................... 24

7.5.1 Capturing Palm prints from Living Persons............................................................................. 26

7.5.2 Capturing Palm Prints from Deceased Persons ...................................................................... 27

7.6 Palm Print Capture of Latent Prints from Objects ........................................................................ 27

7.7 Toe and Sole Capture of Exemplars from Persons........................................................................ 27

7.8 Toe and Sole (Plantar) Capture of Latent Prints from Objects.................................................. 28

7.9 Friction Ridge Interchange Requirements...................................................................................... 28

7.9.1 Image vs. Template ......................................................................................................................... 30

8 Mobile ID 2D Photographic Images................................................................................................... 30

8.1 Basic Equipment Requirements......................................................................................................... 31

8.2 Image Data Handling Requirements – On Device.......................................................................... 33

8.2.1 Still Photograph............................................................................................................................... 33

8.2.2 Video ................................................................................................................................................... 35

8.3 Face Photograph Capture Requirements ........................................................................................ 36

8.4 Face Photograph Transmission Requirements ............................................................................. 37

8.5 Scar / Mark / Tattoo (SMT) Image Capture Requirements ........................................................ 39

8.6 Scar / Mark / Tattoo (SMT) Image Transmission Requirements ............................................. 41

8.7 Forensic Dental Image Capture Requirements.............................................................................. 41

8.8 Forensic Dental Image Transmission Requirements................................................................... 41

8.9 Photographic Image Capture for Other Body Parts...................................................................... 42

8.10 Photographic Image Transmission for Other Body Parts .................................................... 42

8.11 Biometric 2D Photo Verification and Identification -- On Device ...................................... 43

8.12 Biometric 2D Photo Verification and Identification – Off Device....................................... 44

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9 Iris Images................................................................................................................................................ 44

9.1 Iris Capture Devices .............................................................................................................................. 44

9.2 Iris Image Capture ................................................................................................................................. 46

9.3 Iris Image Transmission ...................................................................................................................... 47

10 Voice Signals............................................................................................................................................ 49

10.1 Voice Signal Capture Devices ....................................................................................................... 49

10.2 Voice Signal Capture....................................................................................................................... 49

10.3 Voice Signal Transmission............................................................................................................ 51

11 Multiple Modalities in a Single Unit.................................................................................................. 51

12 Mobile ID Use Cases............................................................................................................................... 52

13 Risk Profiles............................................................................................................................................. 52

13.1 Severe Risk........................................................................................................................................ 54

13.2 Moderate Risk .................................................................................................................................. 54

13.3 Mild Risk ............................................................................................................................................ 55

14 Mobile Device Security & Encryption............................................................................................... 55

14.1 Authentication and Authorization.............................................................................................. 56

14.2 Device and Data Authentication.................................................................................................. 56

15 Communication Protocols ................................................................................................................... 57

16 Environmental Profiles ........................................................................................................................ 58

16.1 Indoor Profile ................................................................................................................................... 58

16.2 Outdoor – Heavy Use (Law Enforcement – like) Profile........................................................ 59

16.3 Outdoor – Rugged Use (Military – like) Profile ....................................................................... 59

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1 Introduction

Version 1 of the Mobile ID Best Practice Recommendation (BPR) was released in 2009. It 

has been referenced in many Government procurement acquisitions and has provided 

information helpful to companies developing mobile ID solutions. This version of the BPR 

builds upon that solid foundation, with the intent of reflecting changes in technology, the 

operating environment and standards since 2009. 

The original BPR played a direct role in the 2011 update of the ANSI/NIST-ITL standard. 

The modality-specific acquisition profiles for fingerprint and iris of the BPR were directly 

incorporated into the standard. 

Although closely tied to the ANSI/NIST-ITL standard in content, this is a separate 

document and may be used independently of the standard.

Although Best Practice Recommendations typically only use ‘should’ (as a 

recommendation), ‘shall’ appears several times in this document. ‘Shall’ appears in places 

where the ANSI/NIST-ITL standard’s transmission format is discussed. It is necessary to 

follow the requirements of that standard in order to be conformant to it. 

This revision modifies the acquisition profiles and adds some new ones, which are also 

reflected in the 2015 Update to the ANSI/NIST-ITL standard1

. 

The original BPR included only face, fingerprint and iris as modalities. Friction ridge 

coverage in the BPR is now extended to include plantars (toe and sole) and imaging of 

latent prints. Investigatory and forensic voice data is now a record type in the ANSI/NISTITL standard, so voice is also included as a modality in this version of the BPR. There are

also new sections specifically devoted to scars / marks and tattoos; forensic dental 

photography using mobile devices; and photography of other body parts. In addition, 

there are special discussions about the use of mobile ID devices to obtain samples from 

deceased individuals. 

2 Scope

A Mobile ID Device, for purposes of this document, is defined as a portable biometric 

acquisition station used by governmental organizations to capture high quality biometric 

samples of one or more modalities from a subject – done in near-real-time at any (even 

remote) location. It is expected to operate in relatively unconstrained conditions. It is 

not intended to be stationary and hardwired to a much larger system. With the advent of 

hand-held technology such as smart phones capable of high resolution photography, 

1 It is available at http://www.nist.gov/itl/iad/ig/ansi_standard.cfm. 

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voice capture, fingerprint capture, and possibly even iris image capture -- the definition 

of mobile ID devices is appropriately extended to include those types of devices. 

The functions performed or supported by the Mobile ID Device are:

• Enrollment

• Identification

• Verification

These devices are used across a wide range of Government organizations, including:

• Law enforcement

• Criminal justice

• Military

• Homeland security

• Benefits and services

Some of the many uses cases for mobile identification technology include:

• First responder identity verification at a disaster scene

• Police checking of biometric databases (fingerprint and / or facial) using a

biometric sample from a subject during a traffic stop

• Forensic image capture – including latent friction ridge prints

• Identification of unknown deceased

The quantitative requirements and specifications of required biometric characteristics 

typically vary by use case, and can be substantially different for each of the areas shown 

above.

This document focuses upon generalized characteristics that can be quantified for 

groupings of use cases. Specific use cases will require further refinement of specifications 

on the part of the procurement and operations teams. 

Readers should also be aware of the Technical Report 30125 “Information Technology – 

Biometrics – Biometrics used with mobile devices” issued by the International 

Organization for Standardization (ISO) and the International Electrotechnical Commission 

(IEC)2. TR 30125 is not quoted in this BPR due to copyright restrictions.

2 http://www.iso.org/iso/home/store/catalogue_tc/catalogue_detail.htm?csnumber=53245

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3 Taxonomy and Definitions

The mobile ID device is comprised of several components that may or may not be 

separate physical elements. This is outlined in the taxonomy shown in Figure 1. 

Figure 1 

Mobile Handheld Device Taxonomy3

The following terms are defined for use in this document:

Acquisition Profile

A set of characteristics for the mobile ID device and its use that is defined by ‘level.’ This 

allows a device manufacturer and a procurement officer to state what combination of 

features is defined in a particular device. In this document, the following are described:

• Face (called ‘Subject Acquisition Profile’ – SAP)

• Fingerprint (called ‘Fingerprint Acquisition Profile’ – FAP)

3 From an internal report of the Department of Homeland Security (DHS), Office of Science and Technology, 

2010 -- provided by DHS for use in this document. Some commentators have suggested updates to this figure 

for purposes of this BPR, including adding ‘microphone’ to biometrics (since voice is included in this document). 

“Data management’ may be appropriate in the Platform column – which could be renamed ‘Data Storage / 

Management’. The International Organization for Standardization (ISO) defines template generation (feature 

extraction) as a part of signal processing. To be consistent with ISO, ‘template generation’ would only appear in 

the Biometrics column. 

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• Palm print (called ‘Palm print Acquisition Profile’ - PAP)

• Iris (called ‘Iris Acquisition Profile’ – IAP)

• Toe and foot print (called ‘Toe and foot print Acquisition Profile – TAP)

Note that there is no corresponding Acquisition Profile for Voice. The

equivalent is the combination of Field 11.003 (Audio object descriptor code /

AOD) and Field 11.008 (Acquisition source / AQS) in the ANSI/NIST-ITL

standard4.

Environmental Profile

The set of specifications related to a particular type of environmental conditions in which

the mobile ID device will be used. These profiles (described in Section 16 Environmental 

Profiles) are:

• Indoor

• Outdoor – Heavy Use (Law enforcement-like)

• Outdoor – Rugged Use (Military-like)

Organization’s Application Profile

Technical specifications developed by specific organizations to control data content and 

format for submissions, based upon the ANSI/NIST-ITL standard. Some examples are5

: 

• EBTS6 for Department of Defense (DoD)

• EBTS for the Federal Bureau of Investigations (FBI)

• IXM7 for Department of Homeland Security (DHS)

• INT-I for INTERPOL

Risk Profile 

The levels established to categorize the public risk associated with the biometric modality 

profiles (See Section 13 Risk Profiles). The risk factors are defined as:

• Severe

• Moderate

• Mild

4 In this document, ‘Field’ refers to a Field in the ANSI/NIST-ITL standard. 5 The latest versions of these profiles (and of biometric standards recognized by the US Government for particular use 

cases) are shown in the “Registry of USG Recommended Biometric Standards” which is available at 

http://www.biometrics.gov/Standards/Default.aspx 6 EBTS means Electronic Biometric Transmission Specification 7 IXM stands for Automated Biometric Identification System (IDENT) Exchange Messages

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Scenario 

A detailed description of the use of the Mobile ID device from a particular end-user point 

of view.

Use Case

A categorization that groups together concepts-of-operation sharing similar 

characteristics. In this document, there are four defined use cases(See Section 12 Mobile 

ID Use Cases). 

4 System Design Considerations

There are several tasks that may be accomplished by a biometric mobile identification 

system. The primary ones include signal or image capture, signal or image processing, 

matching, and ultimately, an output decision that indicates an action to be taken by the 

operator. This action is based on an application-specific decision process. Figure 2

illustrates typical combinations of these tasks across four basic configurations that can be 

used to divide the workload up between the Mobile ID device and a networked system. 

The functions shown below the ‘network’ are not included in the mobile device in that 

particular configuration. 

Figure 2 

Tasks Across Four Basic Configurations

Data Capture

Matching

Network

Signal

Processing

Decision

Data Capture

Matching

Signal

Processing

Decision

Data Capture

Matching

Signal

Processing

Decision

Data Capture

Matching

Signal

Processing

Decision

(a)

(standalone)

(b) (c) (d)

Network

Network

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The primary tasks of signal or image capture; signal or image processing; matching; and 

output decision generation can be performed by the Mobile ID device alone or by splitting 

the workload with a networked system. Factors influencing the operation of these 

functions include location, availability of network connectivity, bandwidth of the network 

connection, processing power, storage capacity of the mobile device, response time 

requirements, auditing / data retention and privacy requirements and interoperability 

with the other systems. (The cloud in Figure 2 represents a network connection.) 

• Column (a) illustrates a standalone approach where the Mobile ID device 

performs all four functions. 

• Columns (b) – (d) illustrate varying degrees of task allocation across a 

networked system. 

The objectives to be accomplished for each of the tasks are:

• Data Capture – The process of acquiring one or more raw biometric samples 

from a subject

• Signal Processing – The process of extracting distinguishing features from a 

raw biometric sample, which may include some or all of the following:

o Signal or image normalization

o Segmentation

o Feature extraction

o Quality assessment

o Template creation8

• Matching – The process of comparing the features extracted from a submitted 

biometric sample to those of one or more reference templates in a database 

and generating a resulting similarity score for each template comparison. 

• Decision – The process of making a match/non-match conclusion based on the 

similarity score(s) meeting or exceeding a specified threshold, the application 

of a more complex decision processing such as multi-biometric fusion, or the 

creation of a candidate list. 

The Decision task should be further interpreted in an application dependent manner. 

Resulting actions may include one or both of the following decision processes:

• Application Level Decision - The result of the search may automatically: 

 

8 For purposes of this document, ‘template’ as a term is inclusive of voice models. 

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o Generate one or more predetermined messages to the operator of 

the device 

o Trigger an alert (to one or more other systems or operators)

o Initiate a search or retrieve additional data from one or more other 

systems (e.g., intelligence systems, facial image databases, etc.) 

o Be passed to a human operator for manual verification

o Be returned as ‘raw’ image data to the operator of the Mobile ID 

device

Note: An application level decision may take place on either or both sides of any 

network.

• Operator Decision - Depending on the specific application and the result of the 

search, the operator of the Mobile ID device may or may not be free to make 

his or her own decision on how to proceed in a particular case. 

o In some scenarios, specific instructions may be returned, e.g., 

‘arrest this person’, ‘do not detain this person’, ‘this is the same 

person as their supplied credential indicates’, or ‘this is not the 

same person as the supplied credential indicates’

o In other scenarios, the search result may be returned to assist the 

operator in deciding what action to take, possibly in conjunction 

with demographic, other metadata, or one or more facial images 

of the potential ‘matches’

Other tasks to be performed, but not illustrated, include the addition of contextual data, 

the formatting of the data (to the ANSI/NIST-ITL standard and an organization’s 

application profiles such as FBI EBTS, DoD EBTS; or to other standard format such as an 

ISO data transmission standard), and the handling of transactions and responses.

There are also administrative tasks that may need to be accomplished. These include 

configuring and calibrating the device for a particular scenario, loading/updating of 

watch-lists, actions to be taken by the operator in different situations, logging of 

encounters, output of log files and other metrics, etc.

The application requirements for the Mobile ID device drive the overall system 

architecture and requirements for individual components of that system. 

Note that there is flexibility in the overall system design shown in Figure 2. As illustrated 

in Figure 3 the ‘Signal Processing’ step may itself be split. In this example, a mobile ID 

device deals with the face, fingerprints and iris modalities. A separate unit deals with 

Rapid DNA (not considered to be a mobile ID device for purposes of this document). The 

output of these two units is combined at a local site to generate a unified transaction for 

a single individual. That transaction is forwarded to a second site, where the full suite of 

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information is added which is necessary for transmission to one or more sites that handle 

the matching. 

Figure 4 illustrates a system architecture where the compressed iris image (only) is 

transmitted to a local station, where more information is added to the transmission to a 

central system for matching and processing. The central system may send back a 

candidate list to the local station for review. Based upon standard operating procedures 

(which may vary over time and operating conditions) a yes / no actionable response is 

sent back to the operator. Thus the telecommunications needs of the mobile unit are at 

an extreme minimum in this design.

Figure 3 

Flexibility in System Design – 

Illustration of Breaking Apart the Signal Processing Step

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Figure 4 

Flexibility in System Design – 

Illustration of Breaking Apart the Signal Processing Step and

Breaking Apart the Decision Step

Many more configurations are possible other than the two illustrated above. As highlighted 

above, the physical design of the Mobile ID device impacts system requirements and 

constraints. Physical considerations include:

• System components connections (or lack thereof) 

• Connectivity to other systems (sharing/interoperability)

• Security aspects of interconnected components

A partial list of design configurations might include one or more of the following within a 

system: 

• Handheld biometric sensors

• Handheld data entry devices

• Handheld communications to a central location

• Handheld communications to a nearby vehicle

• Vehicle-based or other movable-platform-based data entry

• Vehicle-based or other movable-platform-based communications to a central 

location

• Processing power and storage capacity of the mobile device

• Power sources and battery life

• Display size and capability

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The Mobile ID device may be designed and configured to achieve a level of integration 

defined as:

• Fully Integrated (e.g., sensors embedded within the device)

• Mated (e.g., smart phone/tablet with case/sled for rolled fingerprint capture) 

• Tethered-peripheral (e.g., USB fingerprint reader) 

• Physically separate components functioning together (e.g., tablet control of a 

physically separated biometric device, using WS-BD9 protocols)

5 Data Format

Data formats are closely tied to the overall design requirements. Several different data 

formats may be employed within a system. To the extent possible, it is advisable to use 

standardized formats. Even for totally self-contained systems, data formats play a role – 

particularly when a documentary record is to be maintained of the interaction with the 

subject and the result of the match comparison. Typical data format considerations 

include:

• Format for data transport to external systems and / or locations and to import 

data from outside systems and / or locations 

• Format at interfaces of components within a system

• Data compression

• Packet size 

• Network bandwidth, latency

• Storage space (of processed or raw data)

• Data and privacy protection for storage and transmission

• Matching performance (i.e. for template formats)

• Data sharing requirements

• Data secrecy (possibility of security classification levels) and 

• Data authentication.

6 Data Quality

The quality of data is a major factor in how accurately a system can perform. Quality 

assessment may occur at each stage in Figure 2 (automated and/or humanly reviewed). 

Quality is also affected by compression of data. Data shall not be compressed, then 

uncompressed and then recompressed at any point in its life cycle of use. Certain types 

of compression result a substantial loss of data (‘lossy’) while others are considered 

‘lossless’. Only one lossy data compression is allowed without compromising the integrity 

 

9 WS-BD refers to Web Services – Biometric Devices. NIST Special Publication 500-288 (Specification for WS-Biometric 

Devices (WS-BD) Version 1) is available at http://www.nist.gov/itl/iad/ig/upload/NIST-SP-500-288-v1.pdf “WS-BD 

provides a framework for deploying and invoking core synchronous operations via lightweight web service protocols for 

the command and control of biometric sensors.” (Quoted from Section 2 of the document)

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and fidelity of the data. Compression of an image or signal is a major consideration 

affecting the subsequent usefulness of the data, and it is addressed in the requirements 

associated with each modality.

The enrollment (‘reference’) data (which resides in a database – sometimes called the 

‘gallery’ 10) and the probe (which is being compared to the stored data) should be of the 

highest quality possible. Not all biometric modalities have clearly established measures 

of data quality that are predictive of matcher performance. 

 

It is a best practice to attempt to capture the highest quality data possible, noting that 

not all scenarios enable the operator to collect high quality biometric data. Probes may

fail to match against a poor quality enrolled image, or conversely there may be an 

unacceptable number of potential matches that need to be reviewed manually. A poor 

quality probe may likewise fail to match even a high quality enrolled image. 

A best practice recommendation is that an initial image quality assessment should be 

done to provide feedback to the operator during the capture process, whether for 

enrollment or for use as a probe. This may take several forms, such as (but not limited 

to):

• Use of an automated quality assessment tool

• Meter readings on the capture device (such as light levels on a camera and 

background noise levels for a voice-recording device). 

As an example of an automated quality assessment tool, the NIST Fingerprint Image 

Quality (NFIQ) has been historically used in many systems. It is based upon a scale of 1 to 

5 with 5 being the worst value. It is only applicable to fingerprint exemplars (not latent 

friction ridge prints, palm print exemplars or plantar print exemplars). If using NFIQ, it is 

a best practice that images captured with a value of 4 or 5 should not be used for 

enrollment purposes. 

Capture devices may be designed to operate for only one modality or they may be able 

to capture multiple modalities. In addition, they may have different levels of ability for 

the operator to enter metadata (such as the circumstances concerning why the data was 

collected, the subject’s name, etc.) 

Some units may be designed to capture a biometric sample from the subject using one 

modality (such as fingerprint) and also capture a biometric sample from the operator (of 

the same or possibly even a different modality, such as voice) to verify that the operator 

is authorized to use the unit. 

 

10 The database can be anywhere from one sample to millions of samples. 

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7 Friction Ridges 

This section describes the features of a capture unit that are specific to friction ridges. 

7.1 Friction Ridge Capture Devices

Friction ridge capture devices for exemplars (i.e., captured from an individual, not a 

surface) have been used in mobile environments for many years. Since the general 

attributes are similar for all three types of friction ridges (finger, palm and plantar), they 

are grouped together in this document. In fact, some devices can be (and are) used for 

capture of different types of friction ridge prints. There are acquisition profiles that are 

described in Section 7.1.1 of this document. The Fingerprint Acquisition Profile (FAP) 

levels, Palm print Acquisition Profile (PAP) levels, and Toe and foot print Acquisition

Profile (TAP) levels should be specified in record types 14, 15 and 19, respectively, when 

using the ANSI/NIST-ITL standard. 

As discussed in Section 7.4, fingerprints can also be captured from objects (latent prints) 

– or even victims’ bodies using mobile technology. These images can be transmitted in 

record type-13 based upon the ANSI/NIST-ITL standard. Latent prints are sufficiently 

different from exemplars that they are handled separately in the tables of this section. 

Table 1 is from the 2015 Update of the ANSI/NIST-ITL standard. Notice that this table 

concerns impression types, while Table 2 concerns the capture technology. While one 

may imply the other, there is not always a direct correlation between the two. The codes 

in Table 1 should be entered in fields 13.003, 14.003, 15.003, and 19.003 of ANSI/NISTITL transactions. The codes are a subset of the original list of impression types for the 

ANSI/NIST-ITL standard, which is still retained for type-4 records11. Table 2 is excerpted 

from the 2015 Update of the ANSI/NIST-ITL standard. The information in this table can 

optionally be entered in Fields 13.901, 14.901, 15.901, and 19.90112 of ANSI/NIST-ITL

transactions. Note that there is no capability to encode this information in a type-4 

ANSI/NIST-ITL record. 

 

11 Type-4 records should be used only for transmission to legacy fingerprint systems. There is very limited capability to 

include metadata about the image in a type-4 record. 12 These fields are new for the 2015 Update. 

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Table 1 

Friction Ridge Impression Types

Exemplar Prints

Latent Prints

Type Code Description

Contact Impressions

Plain Contact 0 Finger(s) presented still on 

platen

Rolled Contact 1 Finger rolled on platen

Vertical Swipe 8 Finger swiped on platen

Contactless Acquisitions

Plain 

Contactless – 

Stationary 

Subject

24 Finger(s) / palm / plantar 

presented stationary, in view of 

a stationary sensor and sensor 

captures plain contact 

equivalent.

Rolled 

Contactless – 

Moving Subject

25 Finger(s) /palm / plantar rolled 

in view of the sensor

Rolled 

Contactless – 

Stationary 

Subject

41 Finger(s) / palm / plantar 

presented stationary, and 

sensor captures rolled 

equivalent

Plain 

Contactless – 

Moving Subject

42 Finger(s) / palm / plantar move 

though the capture volume of a 

sensor

System Integration Exceptions

Other 28

Unknown 29

Type Code Description

Latent image 4 Image or impression of friction 

skin deposited on a surface

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Table 2 

Friction Ridge Capture Technology

Technology Code Description

Unknown 0 Capture Technology not provided by sensor 

manufacturer

Other 1 Capture Technology not sufficiently characterized by 

table

Optical - Total 

Internal 

Reflection (TIR) 

– Bright Field

3 Using optical angle of incidence effects, a contact 

fingerprint scanner captures ridge information such 

that ridges absorb light, and absence of ridges reflects 

light back to the sensor (dark ridges on a white 

background)

Optical TIR –

Dark Field

4 Using optical angle of incidence effects, a contact 

fingerprint scanner captures ridge information such 

that ridges reflect light (white ridges on a dark 

background)

Optical Direct 

Imaging - Native

5 Light reflected from the friction ridge is imaged, 

resulting in a light gray on darker gray image... This 

may be performed by contact or contactlessly, and 

may incorporate merging of images from multiple 

sensors or from rocking or swaying sensors / subjects.

Optical Direct 

Imaging – Low 

Frequency 

Unwrapped

6 Light reflected from the friction ridge is imaged onto 1 

or more sensors. This may be performed by contact or 

contactlessly, and utilizes the low frequency 3D detail 

to “unwrap” or project the image texture onto a 2D 

grayscale image.

3-Dimensional 

Imaging – High 

Frequency 

Unwrapped

7 High frequency friction ridge information is collected 

(optically, acoustic, etc.), and then “unwrapped” to 

create a 2D image from the 3D point cloud or mesh

Capacitive 9 A contact technology in which the capacitance of the 

fingerprint is assessed via a conducted AC signal

Capacitive –

Radio 

Frequency (RF)

10 A contact technology in which the capacitance of the 

fingerprint is assessed via a radiated RF signal

Electroluminescent 

(EL) Optical 

Direct Imaging

11 A contact technology in which the ridges and an 

Alternating Current (AC) signal cause an EL panel to 

emit light which is captured by an imaging system

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7.1.1 Friction Ridge Acquisition Profiles

Table 3, Table 4 and Table 5 show the acquisition profiles for devices collecting images 

from fingers, palms and feet, respectively. As noted in Table 2, there are many other 

types of capture devices. Contact optical devices may be tested according to protocols 

established by the FBI, and the list of certified products is maintained on the FBI website: 

https://www.fbibiospecs.cjis.org.

13 The acquisition profiles are an easy way to summarize 

a set of characteristics for procurement actions or product fact sheets. The ANSI/NISTITL standard contains fields for the transmission of the acquisition profile specification 

level for optical capture devices used to generate the images. 

It is up to the system designer of each particular application to determine the appropriate 

levels for each of the enrollment, identification, or verification functions especially if there 

is an intention to exchange data with other systems 

A single unit may meet a certain fingerprint acquisition profile (FAP) level, and one for 

palm prints (PAP) and one for plantars (TAP). The concept of acquisition profiles is also 

extended to other biometric modalities beyond those of friction ridges, such as face and 

13 Some non-optical devices have also been tested by the FBI using procedures modified from those developed for 

optical devices. Each such test must be developed with the characteristics of the non-optical acquisition device taken 

into account. The object is to ensure that such a device will yield images comparable or better than an optical device.

Technology Code Description

Reflected 

Ultrasonic 

Image

12 A contact technology in which the friction ridge 

reflects ultrasonic energy which is assessed by the 

sensor

Ultrasonic 

Impediography

13 A contact technology in which the absorption of 

ultrasonic energy is measured by changes in the 

impedance of a piezo-electric material

Thermal 

Imaging

14 A contact technology in which the sensor measures 

the heat reflected from the fingerprint in contact with 

the sensor.

Direct Pressure 

Sensitive

15 A contact technology in which the pressure of the 

fingerprint ridges against a material is measured.

Indirect 

Pressure

16 A contact technology in which the pressure of the 

fingerprint ridges against a deformable material is 

assessed optically to produce a friction ridge image.

Latent 

Impression

18 A capture process in which the digital image of the 

latent impression is acquired directly from the latent 

impression, using a flatbed scanner or digital camera.

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iris. Therefore, a multi-biometric capture unit / system may also list an iris acquisition

profile (IAP) and a subject face acquisition profile (SAP). 

The following sections describe the row entries (specifications) in Table 3, Table 4, and 

Table 5. Note that these acquisition profiles do NOT apply to latent prints. These sections

concern acquisition of a print directly from a person (alive or dead). 

7.1.1.1 Flat Images and Rolled Images

This category is associated with fingerprints. As defined in the ANSI/NIST-ITL standard for 

fingerprints:

• Flat fingerprint: A fingerprint image resulting from the touching of a single 

finger to a livescan platen or paper fingerprint card without rolling motion. 

Also known as a single-finger plain impression. 

• Rolled fingerprint: A fingerprint image collected by rolling the finger across a 

livescan platen or paper fingerprint card from nail to nail.

For units with platens smaller than 1.6” x 1.5”, rolled images should not be captured. It 

should be noted that the very small platens associated with FAP 10 might not capture a 

sufficient area of the fingerprint for certain applications, resulting in a high False NonMatch Rate when compared to a large database. It is strongly recommended that singlefinger units be a minimum level of FAP level 30 14 for mobile applications (other than 

unlocking the mobile device using the embedded sensor). 

7.1.1.2 Gray Levels

This category is applicable to FAP, PAP and TAP tables.

Note that the minimum gray levels are the same for all levels. Grayscale should normally 

be quantized to eight bits (256 gray levels). 

It is a best practice to acquire exemplars using sensors that operate producing grayscale 

images. 

 

14 See NISTIR 7950, “Examination of the Impact of Fingerprint Spatial Area Loss on Matcher Performance in 

Various Mobile Identification Scenarios” March 2014. It is available at 

http://nvlpubs.nist.gov/nistpubs/ir/2014/NIST.IR.7950.pdf. 

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7.1.1.3 Acceptable Image Resolution

This category is applicable to FAP, PAP and TAP tables. The resolution of the images shall 

be either 500 pixels per inch (ppi) or 1000 ppi. A small variance is allowed around these 

two values. For PIV-certified devices, a 2% tolerance level is allowed for 500 ppi devices. 

For Appendix F certified devices, a maximum 1% deviance is allowed from either 500 or 

1000 ppi. 

7.1.1.4 Image Dimension

This category is applicable to FAP, PAP and TAP tables. A principal distinguishing 

characteristic of the various acquisition profile levels is the size of the capture area for the 

friction ridge sample. There is usually a direct relationship between the size of the capture 

platen and the size of the unit itself. However, there is a tradeoff. Small units require 

imaging each finger individually. Additionally, very small units (such as FAP 10) only 

capture a small portion of the fingerprint. By nature, palm and plantar print sensor 

surfaces are larger and may be larger than the units used to capture a four-finger slap 

image. Each operating and data processing / matching agency must determine what 

levels are determined to be acceptable for their operational use. This is usually stated in 

procurement actions using wording such as ‘A minimum of FAPxx (or PAPxx or TAPxx) 

level shall be provided by the vendor for all units delivered under this contract.” 

7.1.1.5 Compression Algorithm 

If compressed, friction ridge images captured at 500 ppi shall use the Wavelet Scalar 

Quantization (WSQ) algorithm for compression prior to transmission and/or storage. For 

platens 3.2” x 1.5” or larger, WSQ Version 3.1 or higher shall be used. Earlier versions of 

WSQ were not adapted for larger platens and can fail to properly handle data around the 

edges of the area of capture. WSQ specifications are contained in WSQ Gray-scale 

Fingerprint Image Compression Specification, October 2010. Friction ridge images 

captured at 1000 ppi shall use the Joint Photographic Experts Group (JPEG) 2000 

algorithm for compression prior to transmission and/or storage. This shall be in 

accordance with the JP2 format as described in ISO 15444-1. NIST Special Publication 500-

289, Compression Guidance for 1000 ppi Friction Ridge Imagery15 provides explicit 

guidance on how to perform these compressions. Some systems can accept and process 

only 500 ppi images. Therefore, if a mobile device captures images at 1000 ppi, the image 

may need to be converted to 500 ppi prior to transmission. This conversion shall be 

performed according to the guidance in “Examination of Downsampling Strategies for 

Converting 1000 ppi Fingerprint Imagery to 500 ppi, NISTIR 7839”16.

 

15 It is available at http://nvlpubs.nist.gov/nistpubs/specialpublications/NIST.SP.500-289.pdf 16 Available at http://www.nist.gov/customcf/get_pdf.cfm?pub_id=912779

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7.1.1.6 Compression Ratio

If an image is over-compressed, it loses salient characteristics that may be useful for 

matching. NIST performed studies on image compression17 that analyzed the levels of 

compression. 

For small images (smaller than 1.6” x 1.5”), a compression of 10:1 is specified at 500 ppi. 

For larger platens capturing at 500 ppi, a ratio of 15:1 is specified. However, at 1000 ppi, 

all platen sizes shall use a ratio of 10:1.

7.1.1.7 Simultaneous Fingers

The ‘simultaneous fingers’ reference in Table 3 is a reminder of the practical implication 

of using a unit that has a platen size corresponding to each particular FAP level.

7.1.1.8 Sensor Certification

Sensor certification can be extremely important in procurement actions. The list of FBIcertified products available at https://www.fbibiospecs.cjis.gov have passed tests to 

establish conformance to specifications for PIV-devices or FBI-EBTS Appendix F 

specifications. Note that some organizations may require devices to be subject to further 

tests. 

 

17 See the studies available at http://www.nist.gov/itl/iad/ig/compression.cfm 

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Table 3 

Fingerprint Acquisition Profile (FAP) Levels 

 

18 Scanner resolutions values specified in pixels per inch (ppi) as well as scanner platen dimensions and capture area 

sizes specified in inches are based on widely used specification guidelines for such devices and is accepted as common 

nomenclature within the industry. SI units for these will not be presented in this document for these values. 19 In ANSI/NIST-ITL prior to 2015, FAP 50 had a minimum dimension of 2.5” x 1.5” and was specified for 1-3 fingers. 

However, no devices were created matching these characteristics, and there was a market presence 

corresponding to the revised FAP 50 specifications in this document and ANSI/NIST-ITL 1-2011 Update 2015. 20 Larger platens require WSQ 3.1 or higher. 21 JPEG2K is required for 1000 ppi images. WSQ was designed for 500 ppi compression only. 22 Up to 4 fingers may be allowed by some systems, if stitched images are acceptable according to the 

Organization’s Application Profile. Some capture units may be capable of taking two images and stitching them 

into one output image. 2 fingers fit without stitching on one image for this size platen. 23 Although technically possible to capture four slap fingers on a FAP 50 device, it requires angling of the fingers, 

which may be problematic for certain systems. Some application profiles actively discourage slanted fingers. The 

FBI states, “All friction ridge prints should be captured as closely as possible to an upright position.”

Capture18 FAP 10 FAP 20 FAP 30 FAP 40

Acquire Flat Images Yes Yes Yes Yes

Acquire Rolled Images No No No Optional

Minimum Gray Levels 256 256 256 256

Acceptable Image Resolution 500 +/- 2% 500 +/- 2% 500 +/- 2% 500 +/- 2%

Minimum Image Dimension 

(W x H) inches

0.5”x.65” 0.6”x 0.8” 0.8”x 1.0” 1.6”x1.5”

Maximum Compression Ratio 10:1 10:1 10:1 15:1

Compression Algorithm WSQ 2.0+ WSQ 2.0+ WSQ 2.0+ WSQ 2.0+

Simultaneous # of Fingers 1 1 1 1-2

Sensor Certification PIV PIV PIV PIV

Capture FAP 45 FAP 50 19 FAP 60 FAP 145 FAP 150 FAP 160

Acquire Flat Images Yes Yes Yes Yes Yes Yes

Acquire Rolled Images Optional Optional Optional Optional Optional Optional

Minimum Gray Levels 256 256 256 256 256 256

Acceptable Image 

Resolution

500 +/- 1% 500 +/- 1% 500 +/- 1% 1000 +/- 1% 1000 +/- 1% 1000 +/- 1%

Minimum Image 

Dimension 

(W x H) inches

1.6”x1.5” 3.2”x2.0” 3.2”x3.0” 1.6”x1.5” 3.2”x2” 3.2”x3.0”

Maximum 

Compression Ratio

15:1 15:1 15:1 10:1 10:1 10:1

Compression 

Algorithm

WSQ 2.0+ WSQ 3.1+ 20 WSQ 3.1+ 20 JPEG2K 21 JPEG2K21 JPEG2K21

Simultaneous # of 

Fingers

1-4 22 1-423 1-4 1-4 1-4 1-4

Sensor Certification Appendix F Appendix F Appendix F N/A N/A N/A

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7.2 Fingerprint Capture Unit Equipment Specifications

Table 3 lists the Acquisition Profile levels for optical capture devices that can be used for 

fingerprint capture24. It is highly recommended that the procuring organization adhere to 

the scanning resolution, gray scale, compression ratios and algorithms specifications of 

the table. When a FAP level is not applicable due to the technology deployed, then the 

user should include the Make and Model of the acquisition unit in Field 14.904 of an 

ANSI/NIST-ITL transaction record when using that record type. 

Mobile devices with the capability to detect the location of the fingerprint are desirable 

to provide a left/right, up/down indication for the operator or subject to insure optimal 

image content. 

Display of fingerprints on mobile device during the capture process is a useful option for 

some mobile device applications.

Mobile devices with the capability to evaluate each image frame captured are desirable 

to determine if a fingerprint is present that meets quality requirements and automatically 

save the image. 

Mobile devices with the capability to manually command the device to capture the image 

currently on the sensor are desirable to insure the ability to capture difficult to image 

fingers. 

After capture of the fingerprint images, an automated quality check function is desirable 

based on a combination of:

• Image photographic properties

• Image size

• Minutiae count

• Core location

• NIST Image quality scores (NFIQ)

Imaging sensors (e.g., optical scanner platen surfaces) that may be field-replaced and 

automatically calibrated are desirable to ensure continuity of use.

Aside from the recommendations and requirements listed above for the fingerprint 

capture device, other factors that affect the performance of these Mobile ID devices and 

systems need to be considered. Many of these relate to training and include:

• Operation of the device within temperature and humidity specifications

 

24 Non-optical devices may be tested and certified on a case-by-case basis, since specialized tests must be developed 

for each – to ensure a suitable level of fidelity. 

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• Ruggedness of the device

• Operator safety 

• Cleanliness of fingers

• Maintain clean sensor surface

• Types of cleaners allowed on sensor surface

• Consistent placement of the same finger(s)

• Optical scanners should avoid excess illumination (or use capture devices that can 

function effectively in full sunlight)

• Procedures to minimize the possibility of finger sequence errors, if enrolling more 

than 1 finger

• Automated quality feedback to operator

• Speed of capture

• How many transactions can be in process simultaneously (can a new set of fingerprints 

be captured while waiting for search results?)

7.3 Fingerprint Capture of Exemplars from Persons

 

This section details the basic requirements for fingerprint capture using mobile ID devices. 

It should be noted that additional requirements could be specified based upon the use 

case. 

7.3.1 Capturing Fingerprints from Living Persons

The ergonomics of fingerprint capture from living persons is an important factor in 

determining which mobile ID device to acquire and how to use it. When procuring a unit, 

the authority should determine which use case or group of use cases is applicable. There 

may be tradeoffs in order to perform multiple operations.

A major factor is whether the subject is likely to be cooperative. Another factor is the 

ability of the subject to self-manipulate his/her fingers(s) (e.g., if handcuffed). 

Placing a finger / fingers upon a platen with the appropriate pressure and area of capture 

is essential for a usable print to be acquired. There should be a presentation screen for 

the operator, and the unit should be capable of being held by the operator, unless the 

concept is to place the unit on a flat surface without holding it. In such a case, the 

operator may be able to physical assist the subject with placing the finger(s) upon the 

platen. 

For uncooperative subjects, such as those in handcuffs, the ergonomics of the capture of 

the prints may dictate a particular physical form for the device. It is likely that the 

operator will have to manipulate the device to and possibly around the subject’s finger(s). 

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• Mobile ID fingerprint devices should be configurable so they can capture the specified 

finger(s) for a particular application.

• Use cases should dictate the number of fingers to be used. 

• When fewer than 10 fingerprints are captured, it is recommended that fingers 2, 3, 7, 

& 8 be used. 

• When possible, capture of 4 fingers is preferable to capture of 2 fingers.

• Enrollments for a system that supports latent searches should include thumbs.

• Fingerprint images captured with dimensions according to lower FAP levels may 

contain only a small area of the fingerprint and thereby may reduce the overall system 

accuracy. This shortfall should be kept in mind and tradeoffs weighed carefully in 

utilizing the lower FAP levels.

7.3.2 Capturing Fingerprints from Deceased Persons

For living persons, the finger(s) are typically brought to the device and may be 

manipulated to acquire the print – such as the operator guiding a subject’s finger to 

produce a rolled print. 

For deceased individuals, the finger(s) may exhibit rigor mortis, be partially decomposed 

and / or dehydrated. This provides challenges to the acquisition of prints with a mobile 

device. There are several choices on how to best acquire the prints, such as (but not 

limited to): 

• Manipulate the device around the finger(s) (with or without re-hydration)

• Sever the finger(s) and press / roll them on the device

• Sever the hand, remove the skin and place an operator’s hand within the skin to 

acquire the prints in a manner similar to acquiring prints from a living person

An excellent reference on the subject is Chapter X of “The Science of Fingerprints” 

(Published by the FBI) called “Problems and Practices in Fingerprinting the Dead”.25 

The quality of the prints may be poor, with little chance of improving the quality – unlike 

with living individuals, when a recapture often provides a better sample. In many cases, 

the captured print will be comparable in quality to that of a latent print – with portions 

of the print unusable for matching. In fact, some jurisdictions submit prints from 

deceased individuals to be processed as latent prints. In such cases, a type-13 record is 

used when transmitting using an ANSI/NIST-ITL transaction. Field 13.046 (Image subject 

condition / SUB) should be completed to indicate that the subject status code (SSC) is D 

(data obtained from a non-living person). The subject body status code shall be recorded 

as either 1 (whole) or 2 (fragment). The subject body class code (SBSC) shall also be 

 

25 Available at http://www.gutenberg.org/files/19022/19022-h/19022-h.htm#CHAPTER_X 

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recorded as either 1 (natural tissue) or 2 (decomposed). There is also a field 14.066 that 

contains similar information items, if the image is good enough to be submitted as a type14 record.

7.4 Capture of Latent Fingerprints from Objects

The equipment used for capture of latent prints from objects is substantially different 

from that used to capture prints directly from an individual. The ANSI/NIST-ITL standard

states: “A latent impression is the digital image of the latent impression that was acquired 

directly from a latent impression, using a flatbed scanner or digital camera.” This 

document does not deal with other means of acquiring latent prints, such as ‘lifts’ or casts 

/ molds. Note that there is no requirement that latent prints be grayscale. In fact, many 

jurisdictions prefer that photographic images of latent prints be in color.

It is best practice to record the make and model of the imaging equipment in Field 13.904 

(Make/model/serial number / MMS) of the type-13 record in an ANSI/NIST-ITL

transaction, which is used to transmit latent print images. 

When acquiring a latent print using photography, the best practice is to have a ruler or 

scale present, and this presence should be indicated in Field 13.018 (Ruler or scale 

presence / RSP). The user indicates whether the scale is in inches (IN), millimeters (MM) 

or BOTH. If known, the user should also include the maker and model of the ruler or scale.

The determination of pixel density of the image is important. ANSI/NIST-ITL Field 13.019

(Resolution method / REM) should be used to state how this was done. However, 

generally, a ruler should be used with mobile ID devices. It is important that the ruler be 

accurate. An example of the American Board of Forensic Odontology (ABFO) scale is

shown in Figure 5 26. The ABFO Reference Scale # 2 27 has been in use since 1988. It was 

designed for imaging of patterned injuries, but may also be useful in imaging latent prints. 

The ABFO # 2 specifications include reflectance values of grayscale – which is important 

for latent images. It is important to note that several manufacturers produce rulers 

resembling ABFO # 2 specifications.

 

26 “Dimensional Review of Scales for Forensic Photography”, 

https://www.ncjrs.gov/pdffiles1/nij/grants/243213.pdf 27 Hyzer WG, Krauss TC, “The Bite Mark Standard Reference Scale – ABFO No.2”, J Forensic Sci. 1988 Mar; 33(2): 

498-506 

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Figure 5 

Sample rulers for Latent Print capture – 

ABFO # 2 (NOT TO SCALE -- DO NOT USE OR COPY)

7.5 Palm Print Capture Unit Equipment Specifications

The capture of palm print exemplars is similar in concept to that of fingerprints. The principal 

differences are:

• The area of the print is larger. 

• The palm is not usually rolled. 

The minimum platen area is 5.0” x 5.0” corresponding to a PAP 70 level (as shown in Table 

4). As with the Fingerprint Acquisition Profiles, there are levels corresponding to 500 ppi 

and to 1000 ppi outputs, with corresponding differences in compression ratio and 

compression algorithm to be used. 

All PAP levels require the ability to capture flat images. Capture of rolled images is 

optional. The minimum grayscale level when specifying a PAP level is 256. 

Not included in these basic specifications are others that will be of interest to the 

procuring agency, including (but not limited to):

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• Weight of the unit

• Ability to capture images outdoors (protection from too much sunlight)

• Ability to withstand environmental conditions typical of the conditions in 

which the unit will be used (dust, heat / cold exposure, humidity, etc.)

• Routine maintenance requirements

Table 4 

Palm print Acquisition Profile (PAP) Levels 

Capture PAP 70 PAP 80 PAP 170 PAP 180 

Acceptable Image Resolution 500 +/- 1% 500 +/- 1% 1000 +/- 1% 1000 +/- 1%

Minimum Image Dimension 

(W x H) inches

5.0” x 5.0” 5.0” x 8.0” 5.0” x 5.0” 5.0” x 8.0”

Maximum Compression Ratio 15:1 15:1 10:1 10:1

Compression Algorithm WSQ 3.1+ WSQ 3.1+ JPEG2K JPEG2K

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7.5.1 Capturing Palm prints from Living Persons

Note that PAP levels 70 and 170 (as shown in Table 4) will require at least 2 impressions to obtain 

a full-palm image set, due to the size of the platen. The FBI states 28: “The entire area of the full 

palm is defined as that area extending from the wrist bracelet to the tips of the fingers and can 

be represented as one or two images to represent the full palm. The lower image shall extend 

from the wrist bracelet area to the top of the interdigital area (third finger joint) and shall include 

the thenar and hypothenar areas of the palm. The upper image shall extend from the bottom 

of the interdigital area to the upper tips of the fingers. This provides an adequate amount of 

overlap between the two images to facilitate subject verification. By matching the ridge 

structure and details contained in the common interdigital area, an examiner can confidently 

state that both images came from the same palm. Because neither plain impressions nor 

identification flat impressions include this common overlapping interdigital area, they should 

never be submitted as upper palm images.” See Figure 6. 

Figure 6 

Palm and Finger Segment Positions

 

28 EBTS Technical and Operational Update #5, Version 10.0.5 Final — June 13, 2015

https://www.fbibiospecs.cjis.gov/EBTS/Approved 

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7.5.2 Capturing Palm Prints from Deceased Persons

As is the case with fingerprints, the condition of the palm may affect the quality of the 

acquired print. If rigor mortis is present in a deceased individual, it may not be possible 

to easily acquire the palm print. The procedures that are to be followed to obtain a palm 

print may vary by jurisdiction. 

7.6 Palm Print Capture of Latent Prints from Objects

The same considerations exist for capturing latent palm prints as for latent fingerprints. 

7.7 Toe and Sole Capture of Exemplars from Persons

The capture of toe and sole (plantar) exemplars is similar in concept to that of 

fingerprints. The principal differences are:

• The area of the print is larger. 

• The foot is not usually rolled. 

This is reflected in the equipment specifications. The minimum platen area is 5.0” x 5.0” 

corresponding to a TAP 70 level (as shown in Table 5). As with the fingerprint Acquisition 

Profiles, there are levels corresponding to 500 ppi and to 1000 ppi outputs, with 

corresponding differences in compression ratio and compression algorithm to be used. 

Not included in these basic specifications are others that will be of interest to the 

procuring agency, including (but not limited to):

• Weight of the unit

• Ability to capture images outdoors (protection from too much sunlight)

• Ability to withstand environmental conditions typical of the conditions in 

which the unit will be used (dust, heat / cold exposure, humidity, etc.)

• Routine maintenance requirements

All TAP levels require the ability to capture flat images. Capture of rolled images is 

optional. The minimum grayscale level is 256. It is important to note that some scanners 

large enough to fit a foot upon have been certified as meeting the optical requirements 

of Appendix F. However, this does not mean that they have been certified for acquisition 

of exemplars. They were designed to scan cards that are fully stationary upon the imaging 

surface during the period of scanning. In addition, placing the weight of a foot upon the 

scanner may not be advisable. There have been no scientific studies performed at the 

date of production of this document that have examined the quality of images captured 

directly from a foot on a scanner. 

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Table 5 

Toe and Sole (Plantar) Print Acquisition Profile (TAP) 

Levels 

Capture TAP 70 TAP 80 TAP 170 TAP 180

Acceptable Image Resolution 500 +/- 1% 500 +/- 1% 1000 +/- 1% 1000 +/- 1%

Minimum Image Dimension 

(W x H) inches

5.0” x 5.0” 5.0” x 8.0” 5.0” x 5.0” 5.0”x 8.0”

Maximum Compression Ratio 15:1 15:1 10:1 10:1

Compression Algorithm WSQ 3.1+ WSQ 3.1+ JPEG2K JPEG2K

Scanners may be capable of taking a direct image of the foot, as well as doing their normal 

function of scanning cards. The capture of toe and plantar prints can be difficult. For small 

infants, a standard sized palm 4-finger slap unit may suffice, which is the same as TAP 70. 

However, larger feet may require taking multiple, possibly overlapping, prints to capture 

the entire friction ridge area of the foot. It is therefore recommended that for larger feet 

the portions of the foot be captured in the following manner:

1) Flat Toes -- all five together

2) Ball of the foot 

3) Heel of the foot

For some individuals, it may be possible to capture the middle of the foot, 

as well. 

7.8 Toe and Sole (Plantar) Capture of Latent Prints from 

Objects

The same considerations exist for capturing latent plantar prints as for latent fingerprints. 

7.9 Friction Ridge Interchange Requirements

 

It is highly recommended that much of the information needed for an ANSI/NIST-ITL

transaction be collected or generated automatically by the collection device. 

Most data exchanges of fingerprint information for law enforcement, military and 

homeland security applications are based upon the ANSI/NIST-ITL standard. 

Organizations have typically refined the standard using ‘application profiles’ to specify 

which record types, fields and information items that they require (which may be optional 

in the standard). Certain application profiles may disallow the use of specific options 

contained in the standard. 

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Some applications, such as e-passports and the Indian UID (Unique Identification) 

program are based upon the International Organization for Standardization (ISO) 19794

suite of standards. The principal differences between the ANSI/NIST-ITL and ISO 19794

standards are the types and amount of metadata associated with the biometric sample

and that the ISO standards handle each modality as a separate transaction but the 

ANSI/NIST-ITL standard allows multiple modalities within a single transaction concerning 

an individual. 

Friction ridge record types in the ANSI/NIST-ITL standard are divided into the following

principal groups:

1) Exemplar Images

a. Fingerprint

i. Type-4 (only recommended for legacy systems)

ii. Type-14

b. Palm prints

i. Type-15

c. Plantar prints

i. Type-19

2) Latent prints

i. Type-13

3) Minutiae – all friction ridge types 

i. Type-9 

In addition, there is the capability to transmit an image that is used to extract the image 

that was used for further processing (such as when multiple prints are in the same image 

and must be segmented first).

4) Original Image 

i. Type-20

It is considered best practice to save the original image. If it is cropped, rotated or 

otherwise prepared for inclusion as a type-13, -14, -15, or -19 image, then the original 

should be transmitted with it in a type-20 record. The method of linking these records 

(the original and the processed one(s) is described in the ANSI/NIST-ITL standard in detail. 

Note that this is particularly useful for latent images with multiple prints in view. 

When multiple fingers are captured in the same image, depending on the specific 

Application Profile requirements, the user may 

• Store the image with all four fingers in a type-14 record, with the segmentation 

coordinates specified. 

• Store the original in a type-20 record and segment each finger for a separate type-14 

record. 

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Record types 13, 14, 15 and 19 contain several fields for metadata associated with an 

image. Type-4 is an older type of record, which is discouraged from use. The type-14 

record should be used for flat or rolled impressions at 500ppi WSQ or 1000 ppi JPEG2K 

(potentially transcoded down to 500 ppi WSQ) and the type-4 logical record (when used 

to transmit to a legacy system) shall be used only for impressions at 500 ppi 

WSQ. However, the record type to be used for either flat or rolled images is dependent 

on the transaction type, the capabilities, and the protocols of the receiving system. The 

sender of the transaction must coordinate with the recipient systems’ owners in order to 

determine whether type-4 or type-14 is appropriate for a particular transaction type and 

for that system. 

7.9.1 Image vs. Template

To support interoperability between systems without sacrificing search accuracy, the 

preferred approach is to transmit the friction ridge image(s), thereby enabling the 

minutiae to be extracted and processed on the system where the matching will take place. 

However there are some cases where a minutiae-based approach may be acceptable or 

where the transmission of images may not be possible (e.g., if the device is only used in 

conjunction with a single algorithm or system or due to network bandwidth limitations).

Mobile ID devices may also be used to verify a person’s identity against an ID card or 

token on which a biometric is stored, and such data may be either image or minutia based. 

When this mode is used, the minutia extractor should be one that has been certified by 

NIST as PIV compliant and interoperable with other templates and systems. These 

extractors were certified as a result of the Minutiae Interoperability Exchange Test 

(MINEX) interoperability tests 29. 

8 Mobile ID 2D Photographic Images 

Mobile ID imaging technology exists that is capable of taking facial images as well as 

images of other body parts that may be useful in identification or verification. In addition, 

such images can be used for documentation and for logging of the identity of the 

operator. An ANSI/NIST-ITL type-10 record is used to convey 2D photographic imagery of 

body parts, including faces, unique body features, scars and tattoos. 

Videos may be collected and conveyed with a type-20 record (Original Source 

Representation) or a type-21 record (Associated Context). The use of video cameras worn 

by law enforcement officers is increasing and is recognized as a vital source of data. 

 

29 http://www.nist.gov/itl/iad/ig/minex.cfm 

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Videos recorded by bystanders and by surveillance cameras have also proven to be 

helpful in law enforcement applications. 

If videos are used to extract still images for forensic or automated comparison or analysis, 

then they are conveyed with a type-20 record. If they are used to extract voice 

information for a type-11 record, they shall also be conveyed with a type-20 record. 

However, if the video is used as the voice recording itself, it shall be conveyed with the 

type-11 record. In such a case, the visual content of the video is not used for processing. 

By placing a video in type-20, the audio content can be specified and described in the 

type-11 record, and the individual frame images can be described in a type-10 record.

Since iris image equipment is relatively specialized and the data is transmitted in an 

ANSI/NIST-ITL type-17 record, that category is treated separately in this document. 

3D image capture and specialized techniques such as LIDAR are not addressed in this 

document. However, if they are utilized, the imagery from those units shall be 

transmitted in an ANSI/NIST-ITL type-22 record (Non-photographic imagery data record). 

Although photographic techniques can be used for fingerprint (and other friction ridge) 

acquisition, they are not covered in this section. Such techniques are covered in Table 1 

under codes 24 (Plain contactless – stationary object) and 42 (Plain contactless – moving 

object).

8.1 Basic Equipment Requirements

Additional requirements may be needed to meet the specific situational needs for 

particular use cases, operating conditions and organizational standard operating 

procedures.

This section addresses only certain minimum requirements for 2D photographic image 

capture. Additional requirements are determined by the use cases / agency policies / 

legal requirements and other factors. Table 6 lists the minimum requirements for Mobile 

ID photographic capture equipment. 

Although most cameras (both still image and video) are digital, it is possible to use film 

cameras in mobile ID situations. For digital cameras, the cameras should store the date 

and time in the header of the image. It is highly recommended to also store the GPS 

location (accessed automatically by the camera) with the image data, if possible. 

Table 6 refers to cameras used to capture still photographs, and not videos. These 

requirements are mandatory for still image face capture if the SAP levels 32, 42 or 52 are 

met (as shown in Table 7). 

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A recommended, but optional, feature is a xenon flash or an LED / fill-in flash. The 

ambient light and exposure time are naturally correlated. It is recommended that the 

ambient light be 4 lux and that the exposure time be less than .0

Table 6 

Mobile ID Still-Frame Photographic Requirements

 Factor Comments

Capture distance in cm 60-200 cm (~ 2 – 6 feet), the longer distance is 

preferred

Wavelength range Visible light. 380-780 nanometers

Table 7 

Mobile Device Face Subject Acquisition Profile (SAP) levels

Capture Comments

Levels

32 42 52

Capture device color 

space

Minimum of 24-bit RGB 

color space or a 

minimum of 12-bit 

monochrome color 

space

Minimum of 24-bit RGB 

color space or a 

minimum of 12-bit 

monochrome color 

space

Minimum of 36-bit RGB 

color space or a 

minimum of 12-bit

monochrome color 

space

Image resolution (size) Lower resolution may 

reduce accuracy

> 480 x 600 > 786 x 1024 > 2400 x 3200

Capture device 

controls

Auto gain and auto 

shutter, optional: 

control loop for camera 

parameter (shutter 

speed / flash intensity)

based on face area onboard

Auto gain and auto 

shutter, optional: 

control loop for camera 

parameter (shutter 

speed / flash intensity) 

based on face area onboard (requires 

continuous face 

detection)

Auto gain and auto 

shutter, optional: 

control loop for camera 

parameter (shutter 

speed / flash intensity) 

based on face area onboard (requires 

continuous face 

detection)

Photo composition

Pose of the subject ‘Head’ or ‘Head and 

Shoulders’

At least one full-frontal 

‘Head and Shoulders’ 

image

At least one full-frontal 

‘Head and Shoulders’ 

image

Horizontal:Vertical 

Ratio

4:5 3:4 3:4

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Capture Comments

Levels

32 42 52

Compression algorithm

JPEG. Maximum 

compression ratio 15:1 

for the region of 

interest comprising the 

exposed skin of the 

face, from crown to 

chin ear-to-ear. The 

non-facial portion of 

the image may be 

compressed up to a 

ration of 120:1. Best 

practice is to apply 

lossless compression to 

the frontal image with 

the ears visible.

JPEG 2K. Maximum 

compression ratio 15:1 

for the region of 

interest comprising the 

exposed skin of the 

face, from crown to 

chin ear-to-ear. The 

non-facial portion of 

the image may be 

compressed up to a 

ration of 120:1. Best 

practice is to apply 

lossless compression to 

the frontal image with 

the ears visible.

JPEG 2K. Maximum 

compression ratio 15:1 

for the region of 

interest comprising the 

exposed skin of the 

face, from crown to 

chin and ear-to-ear. 

The non-facial portion 

of the image may be 

compressed up to a 

ration of 120:1. Best 

practice is to apply 

lossless compression to 

the frontal image with 

the ears visible.

Inter-eye distance Lower resolution may 

reduce accuracy

> 90 pixels > 150 pixels > 300 pixels

8.2 Image Data Handling Requirements – On Device

Several photographic imagers (cameras) have the capability to store uncompressed or 

compressed or both types of images. In addition, some units allow adjustments to 

compensate for exposure, color variation, to do cropping and other adjustments upon the 

original image. It is considered a best practice to store the uncompressed image and 

retain it for archival purposes, even if a lossy compressed image is to be transmitted. 

8.2.1 Still Photograph

There is no need for an ANSI/NIST-ITL format to be generated directly by the image 

capture device. Normally, the photographic image would be captured and later formatted 

into an ANSI/NIST-ITL transaction prior to relaying to another site. 

A digital photograph should not be post-processed from the camera’s storage format to 

another format for transmission. However, it is recognized that some cameras store 

images in non-standard formats, and it may be necessary to change the format 

(compression) so that the recipient of the image can ‘read’ and use the image.

Note that some mobile units may not meet the requirements of SAP 32, 42 or 52 as shown 

in Table 7. In such case, the SAP level shall be entered as Level 20 (Legacy mugshot). This 

is used if a mugshot does not fully conform to the SAP level 32 requirements. This would 

be the case, for instance, if the output of the camera were in a TIFF format. 

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Note that while cropping is allowed on the original image prior to submission, the size 

and resolution requirements still apply to the cropped image.

For both JPEG and JPEG2K, care must be taken to account for automatic compression by 

camera hardware. Multiple compression stages can degrade the quality of photographic 

data. 

Note that there are two fields relating to the date of capture of the image in record type10. Although optional, it is considered best practice to enter the date and time of capture 

of the photo in Field 10.005 (Photo capture date / PHD). The mobile camera should 

automatically capture the date & time information. If, however, the exact date and/or 

time is not known then the approximate date and time shall be entered in this field, and 

Field 10.034 (Imagery capture date range estimate / ICDR) shall be entered into the 

record. This field records the amount of time (plus and minus) of which the PHD is the 

center point during which the image could have been originally collected. 

The geographic location of the video capture should be entered into Field 10.998 

(Geographic sample acquisition location / GEO). 

When transmitting a still image, Field 10.996 (Hash / HAS) should also be entered. It has 

a value calculated using SHA-256 calculated upon the contents of Field 10.999 or the 

image stored at the location referenced by Field 10.994. This assists the receiving 

organization to verify that the data has not been altered during transmission. 

Field 10.904 (Make / model / serial number / MMS) should also be completed with the 

relevant information about the camera, if at all possible. 

If the still image is derived from a video, then Field 10.997 (Source representation / SOR) 

should be completed with the cross-reference index to the appropriate type-20 record 

in the transaction containing the original source video from which the still image was 

derived. 

All still digital images transmitted in a type-10 record shall include the following:

• Field 10.002 (Information Designation Character / IDC) – usually automatically 

generated)

• Field 10.004 (Source agency / SRC)

• Field 10.005 (Photo capture date / PHD) – described above

• Field 10.006 (Horizontal line length / HLL)

• Field 10.007 (Vertical line length / VLL)

• Field 10.008 (Scale units / SLC)

• Field 10.009 (Transmitted horizontal pixel scale / THPS)

• Field 10.010 (Transmitted vertical pixel scale / TVPS)

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• Field 10.011 (Compression algorithm / CGA)

• Field 10.012 (Color space / CSP)

• Field 10.999 (Body part image / DATA)

Fields 10.005 through 10.012 listed above are normally captured and derived from the 

data header of the still image from the camera and entered by the transmission data 

generation software. That software is normally also pre-programmed to include the 

value for Field 10.004. Thus, the requirement to know this data should not be a burden 

upon the operational agency.

8.2.2 Video

Video is becoming more ubiquitous in mobile operations. With the advent of lapelcameras and mobile phone devices with video recording capability, this type of digital 

recording has become important to be able to transfer and analyze. It is best practice to 

have the position location (GPS) and time automatically recorded by the video unit. 

There is no need for an ANSI/NIST-ITL format to be directly generated by the video device.

Normally, video would be captured and later formatted into an ANSI/NIST-ITL transaction 

prior to relaying to another site. The remainder of this section describes the basic 

information that should be transmitted in an ANSI/NIST-ITL transaction.

Videos may be entered in type-20. This is particularly useful if they serve as sources for 

still images. Individual frames used for facial, tattoo or other body part images are then 

transmitted in a type-10 record. 

Field 20.904 (Make / model / serial number / MMS) should be completed with the 

relevant information about the video camera, if at all possible. 

Although most video units are digital, it is possible to use film video cameras. The storage 

location of videos from non-digital sources may be stated in Field 20.994 (External File 

Reference EFR). 

Note that it is possible to have a type-20 record linked to another type-20 record – such 

as an extract of the video contained in one record, and the entire recording referenced in 

another (usually stored offline with a pointer to the storage location in the type-20 

record). This relationship is indicated by an entry of “S” in Field 20.003 (SRN cardinality / 

CAR) for the original source type-20 record. 

Video conveyed with a type-20 record may be stored in any format that is the output of 

the recording device. Digital output should not be transcoded into another digital format. 

Field 20.014 (Acquisition source / AQS) has three codes specific to mobile video:

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8 = Video sequence from an analog video camera, stored in analog format

9 = Video sequence from an analog camera, stored in digital format

10 = Video sequence from a digital video camera

Note that there is a code for mobile telephone allowed in Field 20.014. However, it is 

denoted as an audio source, and not a source for video. Use of a mobile telephone with 

a video shall be indicated as Code 10. 

For analog files, it is possible to keep the analog recording (such as on a tape) at a specified 

location. Reference to that location is made in Field 20.994 (External file reference / EFR). 

The data itself need not be contained in the transmission file. This is also true of digital 

files. For extremely large digital files, the preferred method is to have the data stored in 

a file that may be remotely accessed in a secure manner. 

Field 20.015 (Source representation format / SFT) is required for video data. It specifies 

the digital format (such as AVI) or, for analog, it is specified as “ANALOG”. The second 

information item allows the user to specify any special decoding information, if special 

keys are needed to access the data, etc.

If the analyst desires to mark relevant portions of the video recording that are of special 

interest, up to 99 such markings can be entered in Field 20.019 (Time index / TIX). The 

data elements of this field are the start and end times for each segment. 

Note that there are two fields relating to the date of capture of the video in Record Type20. Although optional, it is considered best practice to enter the date and time of capture 

of the video in Field 20.005 (Source representation date / SRD). This should be 

automatically captured by the mobile video camera. If, however, the exact date and/or 

time is not known then the approximate date and time shall be entered in this field, and 

Field 20.022 (Imagery capture date range estimate / ICDR) shall be entered into the 

record. This field records the amount of time (plus and minus) of which the SRD is the 

center point during which the video could have been originally collected. 

The geographic location of the video capture should be entered into Field 20.998 

(Geographic sample acquisition location / GEO). 

When transmitting a video, Field 20.996 (Hash / HAS) should also be entered. It is 

calculated using SHA-256 on the video data in Field 20.999 or the video stored at the 

referenced location stated in Field 20.994. This assists the receiving organization to verify 

that the data has not been altered during transmission. 

8.3 Face Photograph Capture Requirements

Annex E of the ANSI/NIST-ITL standard describes the requirements for facial capture. In 

that Annex, there are specific statements when a section is not applicable to mobile ID 

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(such as for Background and Lighting). The Annex refers to Subject Acquisition Profile 

(SAP) levels, which for mobile ID photographic devices are 32, 42 or 52.30 Specifying the 

SAP level is a mandatory field for face images (Field 10.013), but is not specified for other 

body part images. Table 7 lists only those SAP levels that refer to mobile ID devices. 

Only one face per image is allowed. Digital zoom (interpolation) shall not be used for 

facial images. The face should be in focus from the nose to the ears, which may result in 

the background being out of focus. Lighting should be evenly distributed over the face, if 

possible. It is recognized that this may be difficult to achieve in outdoor settings. The 

subject should be posed full frontal, preferably with a ‘head and shoulders’ composition 

or a ‘head only’ configuration. Head coverings, including hats and scarves should not be 

worn. The full face and ears should be displayed. Hair should be moved to reveal the 

subject’s ears. The subject should have a neutral expression, with the mouth closed and 

eyes open. 

Every effort should be made to capture the face image for enrollment without glasses. 

When possible, images taken for comparison to a database (probes) should also be taken 

without glasses. Note that this recommendation does not prohibit the wearing of glasses 

in facial images. Whether to allow any subjects to wear glasses is a policy decision 

dependent upon local needs, conditions, and legal restrictions. The wearing of eye 

patches is allowed only for medical reasons.

The Mobile ID face capture device must be able to measure the face image quality or to 

provide some means by which the device operator can assess the quality of the captured 

face image. The best practice recommendation is that an automated initial image quality 

assessment should be done to provide feedback to the operator during the capture 

process. Since there is no standard, recognized set of quality measures for facial photos, 

the mobile device should, at a minimum, allow the operator to review the image visually, 

and determine if a re-take is warranted. The operator should visually determine if the 

subject is in focus, has eyes open, is in a full-frontal pose with a neutral mouth expression, 

that there are no ‘hot spots’ on the face, and that the photo is consistent with a faceonly or head-and shoulder image composition. 

8.4 Face Photograph Transmission Requirements

There is no need for an ANSI/NIST-ITL format to be directly generated by the image 

capture device. Normally, the photographic image would be captured and later 

formatted into an ANSI/NIST-ITL transaction prior to relaying to another site. An 

ANSI/NIST-ITL packaging tool normally generates the information in this section.

 

30 It is possible to transmit a still frame that contains a face, tattoo or other body part image from a video. However, 

such an image is not considered to be SAP level 32, 42 or 52. It is considered SAP 0.

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Table 8 lists the fields in ANSI/NIST-ITL that are mandatory for some or all of the SAP 

levels associated with still imagery. Note that this applies ONLY to images that are 

characterized as IMT=FACE. For IMT=FACE, it is highly recommended that the pose be F 

(full face frontal). In such case, Field 10.021 (Pose Offset Angle / POA) is not entered. 

Table 8 

Required ANSI/NIST-ITL Type-10 fields for face images

Mnemonic Condition Test

Field 

Number Field Name

SAP Mandatory with Field 

10.003 (Image type / 

IMT) is FACE

10.013 Subject acquisition profile

POS Mandatory with Field 

10.003 (Image type) is 

FACE

10.020 Subject pose

POA Mandatory if Field 10.20 

has a value of ‘A’ 

(angled)

10.021 Pose offset angle

PAS Mandatory if SAP 42 or 

52 and IMT = FACE

10.023 Photo acquisition source

SXS Mandatory if SAP 42 or 

52 and IMT = FACE

10.026 Subject facial description 

SEC Mandatory if SAP 42 or 

52 and IMT = FACE

10.027 Subject eye color 

SHC Mandatory if SAP 42 or 

52 and IMT = FACE

10.028 Subject hair color 

For facial images captured as SAP 42 or 52, Field 10.026 (Subject facial description / SXS)

shall be entered. It is a mandatory field in ANSI/NIST-ITL. In reality, for mobile

applications, a complete description would require an operator to stop and fully analyze 

each photograph or still image from a video. It is therefore recommended that this field 

be populated as ‘UNKNOWN’ for mobile applications.

The subject’s eye color is mandatory for SAPs 42 and 52. Like the facial description, it 

may be impractical for the operator to write down or otherwise tabulate the eye color 

of subjects whose images he/she has captured in the field. It is therefore recommended 

that the mobile unit automatically populate the eye color code as ‘XXX’ for Unknown. 

For facial images captured as SAP 42 or 52, the subject’s hair color shall be entered. One 

or two attribute codes may be selected. It is impractical for operators in the field to 

record hair color for the subjects that they image. Therefore, it is recommended that 

the code ‘XXX’ for ‘Unknown or unspecified’ be automatically entered.

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The possible values for Field 10.023 (Photo acquisition source / PAS) – which is 

mandatory for SAPs 42 and 52 – are listed in Table 9. If a video is captured and a frame 

extracted later from it to transmit, then TYPE20 is selected. ANALOG VIDEO and DIGITAL 

VIDEO are selected only if the original video is not included in a type-20 record. If a 

‘freeze frame’ is captured at the time of recording, it is entered as a static photograph 

from a digital still-image camera. The codes ‘DIGITAL CAMERA’ and ‘DIGITAL VIDEO’ 

should be able to be added automatically into the field since the source of the data is 

known. This should require no manual intervention on the part of the operator. 

Table 9 

Acquisition source type code

Acquisition source type attribute Attribute code

Unspecified or unknown UNSPECIFIED

Static photograph from an unknown source UNKNOWN PHOTO

Static photograph from a digital still-image camera DIGITAL CAMERA

Static photograph from a scanner SCANNER

Static video frame from an unknown source UNKNOWN VIDEO

Single video frame from an analog video camera ANALOG VIDEO

Single video frame from a digital video camera DIGITAL VIDEO

Vendor specific source VENDOR

Record TYPE-20 original source representation TYPE20

Another source image OTHER

8.5 Scar / Mark / Tattoo (SMT) Image Capture Requirements

The image should only contain the SMT and the surrounding skin and should not contain 

anything else in the background, including patterned walls and floors, furniture, or other 

body parts. If elimination of the background is not possible, the background should be 

plain in order to prevent pattern distractions. 

For purposes of the ANSI/NIST-ITL standard and this document, a tattoo is an indelible 

image that was applied to the skin. A common tattoo results from picking of the skin with 

a coloring material. A subclass of tattoo is chemical, which indicates that the pattern was 

created by the use of chemicals to burn the image into the skin. Another subclass of 

tattoo is branded which indicates that the pattern was caused by using a branding iron or 

other form of applied heat. A third subclass of tattoo is cut which indicates that the image 

was caused by incision of the skin.

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Piercings, implants, birthmarks and scars caused by accidents / medical procedures, etc. 

are all classified as SCAR. A MARK only refers to patterns of needle marks on the skin. 

SMTs can be captured from the front, side, or back of the subject, depending on the body 

location. SMTs on body limbs should be captured with the body part parallel to the torso. 

For example, a tattoo on a forearm should be photographed with the arm pointing 

towards the ground. A tattoo on a leg should be collected with the subject standing 

upright. Different tattoos on distinctively separate body locations should be collected as 

separate photos, except for full body tattoos that are connected across multiple body 

locations. The tattoo should be centered in the photograph and occupy at least 75% of 

the entire image. Thus, the ‘standoff distance’ from the tattoo may differ depending 

upon the size of the tattoo imaged.

Whenever possible, the SMT image should be taken under uniform lighting and be in 

focus with good contrast against the skin. For low contrast or faded tattoos, it may be 

desirable to photograph the tattoo with and without camera flash and select the better 

photo.

The mobile SMT capture device must be able to provide some means by which the device 

operator can assess the quality of the captured SMT image. The best practice 

recommendation is that an initial image quality assessment should be done to provide 

feedback to the operator during the capture process. Since there is no standard, 

recognized set of quality measures for SMT photos, the mobile device should, at a 

minimum, allow the operator to review the image visually, and determine if a re-take is 

warranted. The operator should visually determine if the SMT is in focus, has uniform 

illumination, shows good contrast, and that there are no background or clothing 

distractions in view.

The following paragraphs in Annex E, Section 3 (Photographic requirements) of the 

ANSI/NIST-ITL standard are applicable for SMT images:

 

• E 3.1 Depth of field

• E 3.2 Subject lighting

• E 3.3 Background and lighting

• E 3.4 Exposure calibration 

• E 3.5 Exposure 

• E 3.6 No saturation

• E 3.7 No unnatural color

• E 3.8 No color or grayscale enhancement

• E 3.9 Distortion and angle of view

• E 3.10 Allowed color space

• E 4.15 Medical conditions.

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It may also be desirable to have an image of a large tattooed or scarred area, and an 

image of a smaller portion of the SMT (such as a detail of the tattoo that could be useful 

for determining gang affiliation). There is a field in the type-10 record (Field 10.039 Type10 reference number / T10) that is used to link two or more images of the same SMT by 

using the same index reference for all of the associated images in a transaction. This is 

particularly true when a full ‘sleeve’ or the back is covered. Each significant portion 

should be imaged and described separately, along with an image of the entire area. 

8.6 Scar / Mark / Tattoo (SMT) Image Transmission

Requirements

There is no need for an ANSI/NIST-ITL format to be generated directly by the image 

capture device. Normally, the photographic image would be captured and later 

formatted into an ANSI/NIST-ITL transaction prior to relaying to another site. The user 

should be able to record the location on the body of the SMT.31 For tattoos, there should 

be an option to record its color(s).

8.7 Forensic Dental Image Capture Requirements

There are no special requirements for forensic dental image capture other than the 

image being in focus and including sufficient detail to make the image useful for future 

analysis.

8.8 Forensic Dental Image Transmission Requirements

Mobile units are now used to record images for forensic use, including dental forensics. 

This BPR focuses upon standard, commercially available cameras and not specialized 

equipment (such as portable x-ray equipment).

There is no need for an ANSI/NIST-ITL format to be generated directly by the image 

capture device. Normally, the photographic image would be captured and later 

formatted into an ANSI/NIST-ITL transaction prior to relaying to another site. 

The type-10 record shall indicate the type of forensic dental image as ‘EXTRAORAL’, 

‘INTRAORAL’, ‘LIP’ or ‘MISSING’ in Field 10.003. MISSING is used when an image is taken 

to illustrate that a body part is not present that would normally expected to be present, 

such as a lower jaw. 

For forensic dentistry applications, the subject is normally deceased. Field 10.046 

(Image subject condition / SUB) shall be completed. For deceased individuals, a value 

 

31 An ANSI/NIST-ITL formatting generator should take the body part location recorded by the user and ‘translate’ it to 

the NCIC codes for the SMT body parts, which are listed at http://www.oregon.gov/OSP/CJIS/NCIC.shtml 

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of ‘D’ is entered into the subject status code / SSC. The subject body status code / 

SBSC shall have be 1 when there is an entire body and 2 when the image is of a body 

fragment. The third information item is subject body class / SBCC. Its possible values 

are:

• 1 = natural tissue

• 2 = decomposed

• 3 = skeletal

For lip images, Field 10.049 (Cheiloscopic image data / CID) should be completed. The 

lip print characterization is specified in this field. Note that lip pathologies and 

peculiarities may also be specified in this field, including codes for cleft lip, scars, 

herpetic lesions, tattoos and piercings. 

Field 10.050 (Dental visual image data information / VID) shall be completed if an 

image type of ‘EXTRAORAL’ or ‘INTRAORAL’ is entered in Field 10.003. There is a table 

in the ANSI/NIST-ITL standard that lists the different view positions that may be 

encoded for the photos. Descriptive text may also be entered. 

8.9 Photographic Image Capture for Other Body Parts

There are no special requirements for image capture of other body parts than the 

image being in focus and including sufficient detail to make the image useful for future 

analysis. 

8.10 Photographic Image Transmission for Other Body Parts

Type-10 records may also be used to transmit images of body parts other than of the 

face or oral region. This is particularly useful for deceased individuals. In such cases, 

Field 10.046 (Image subject condition / SUB) shall be completed. For deceased 

individuals, a value of ‘D’ is entered into the subject status code / SSC. The subject 

body status code / SBSC shall have a value of 1 for when there is an entire body and 2 

when the image is of a body fragment. The third information item is subject body class 

/ SBCC. Its possible values are:

• 1 = natural tissue

• 2 = decomposed

• 3 = skeletal

The possible image types that are:

FRONTAL-C (clothed) FRONTAL-N (nude) TORSO-BACK HANDS-PALM 

REAR-C (clothed) REAR-N (nude) TORSO-FRONTHANDS-BACK 

GENITALS BUTTOCKS RIGHT LEG LEFT LEG

RIGHT ARM LEFT ARM HEAD CHEST

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FEET

There are three other categories that may be used: CONDITION, MISSING, and OTHER.

MISSING is used to image a section of the body where a part normally should be, such 

as when an arm has been ripped off of a person, and a picture is taken of the ‘arm’ area 

showing the damage. The list of NCIC codes that correspond to CONDITION are 

indicated in the ANSI/NIST-ITL standard in the description of Field 10.003. Examples are 

POCKMARKS, and HERMAPHR. The NCIC codes for OTHER are also listed in the 

description of Field 10.003. It covers such values as COLOST, BRACE and TRANSVST. 

The NCIC code that is associated with CONDITION, MISSING or OTHER should be entered 

in Field 10.040 (NCIC SMT code / SMT). 

Images of patterned injuries are conveyed in type-10 records. Patterned injury images 

should include an ABFO #2 Reference scale in the image. The part of the body where 

the injury is located is indicated in Field 10.003, and may include FACE as well as the 

categories listed above. (Note SCAR, MARK, TATTOO, MISSING, OTHER and 

CONDITION shall not be entered for patterned injuries). A description of the patterned 

injury may be entered in Field 10.048 (Suspected patterned injury detail / PID). 

8.11 Biometric 2D Photo Verification and Identification -- On 

Device

On-device comparison is most commonly used for one-to-one comparisons -- that is to 

verify the claimed identity of an individual. This may be useful for verification of the 

identity of the operator.

Comparing an image captured of a subject ‘in the field’ on a mobile device to a 

database of known individuals’ images can be performed on the device for a relatively 

small gallery of pre-enrolled images. Such a capability could be useful for operations 

with a ‘closed set’ of subjects – such as those in a detention center or asylum camp. 

On-device algorithms capabilities vary and should be carefully tested and adapted for 

the operational environment. There may be options to present the two or top five 

candidates, or a default to only the top ranked person. 

To date, there have not been extensive evaluations of on-board facial recognition 

systems. Some such systems are entirely proprietary – making evaluation difficult. 

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8.12 Biometric 2D Photo Verification and Identification – Off 

Device

Some mobile systems are designed to relay an image to a central processing site, which 

then compares the photo to a gallery or galleries. The bandwidth required to send a 

photo is a factor, but that is becoming less of an issue with the introduction of better 

mobile telecom service. Some systems are designed to relay back a set of high matching 

photos (i.e., those above a certain score level) or a fixed number of candidates (such as 

5). The operator can then compare the photo and associated information (sex, age, 

date of photo etc.) to make an evaluation as to whether an identity is likely to have been 

established for the subject. This capability can be of great use for officers who need to 

make a judgment as to whether to apprehend a person based upon an outstanding 

warrant, etc. 

Off-unit verification systems should be carefully evaluated prior to purchase. NIST has 

run the Face Recognition Vendor Test (FRVT) several times. NIST has also conducted 

several other face recognition studies – including the Point and Shoot Face Recognition 

Challenge (PaSC). These studies can be accessed through the website 

www.nist.gov/itl/iad/ig/face.cfm. 

9 Iris Images

Iris images are treated separately from other images, since they involve non-visible 

wavelengths and have markedly different data storage and transmission requirements. 

A normal camera, such as can be used for photographs described above, should not be 

used for iris capture. 

9.1 Iris Capture Devices

While it may sometimes be possible to compare iris images taken solely in the visible light 

frequencies, darker irises normally require infra-red imaging to highlight the features of 

the iris that are used for comparison. Thus, a mobile ID unit used for iris capture shall be 

based upon near-infrared wavelength capture (approximately 700 to 900 nm). Some 

systems may use a portion of this range, which is acceptable. 

Mobile ID iris image capture devices typically provide near-infrared lighting using LEDs to 

illuminate the iris. Illumination shall be compliant with illumination standard IEC 825-1 

and safety specification ISO 60825-1. The illumination wavelengths shall have > 90% of 

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energy within the 700 nm to 900 nm band; and > 35 % of energy in the 800 nm to 900 nm

band. 32

Many contemporary iris imagers are capable of capturing both left and right iris images 

simultaneously or quasi-simultaneously (within a few milliseconds). Others capture only

one iris at a time. For mobile applications, both images should be captured 

simultaneously or quasi-simultaneously, with the imager held in an upright position. This 

reduces the possibility of mislabeling of the individual images (right or left). It also allows 

for more accurate estimation of the roll angle and potentially higher accuracy and 

comparison speed. 

In order to achieve acceptable time-to-capture and Failure to Acquire (FTA) rates, the iris 

image sampling frequency must be at least 5 frames per second. The iris image capture 

sensor shall use progressive scanning. The ability for an iris image capture device to 

suppress motion blur and to freeze motion, is a function of exposure time. The maximum 

allowable value for the exposure time, expressed in milliseconds, reduces as Iris 

acquisition profile (IAP) levels increase, from a maximum of 33 ms at IAP 20 to a maximum 

of 10 ms at IAP 40, as shown in Table 10. 

 

32 These band wavelength specifications correspond to those of ISO/IEC 29794-6 and the 2015 Update of the ANSI/NISTITL standard.

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Table 10

Iris Acquisition profiles (IAP)

Capture

IAP Levels

10 11 12 20 30 40

Iris diameter 

in true, nonupscaled pixels

≥ 140 ≥ 170 ≥ 210

Number of 

(quasi-) 

simultaneously 

captured eyes

≥ 1 ≥ 1 2

Spatial 

sampling rate

10 pixels / 

mm. 33

Up sampling 

allowed from 

10 pixels / 

mm if 

algorithms 

require 

higher 

minimum iris 

diameter in 

pixels

Up sampling 

allowed from 

10 pixels / 

mm if 

algorithms 

require 

higher 

minimum iris 

diameter in 

pixels

Exposure time ≤ 33 ms ≤ 15 ms ≤ 10 ms ≤ 33 ms ≤ 15 ms ≤ 10 ms

In order to achieve acceptable recognition accuracy, the iris acquisition sensor must 

achieve a signal-to-noise ratio of at least 36dB. Mobile iris image capture devices can be 

configured differently with regard to the operator interface, in terms of the viewfinder 

(being external or internal) and the manner of providing image quality feedback to the 

operator. These factors will influence the rate of successful captures. The best practice 

recommendation is that an initial image quality assessment should be done to provide 

feedback to the operator during the capture process. The device should alert the operator 

if the captured iris image is of insufficient quality. 

9.2 Iris Image Capture

In order to be considered acceptable as non-intrusive and to avoid excessive geometric 

distortion, the minimum distance between the mobile iris capture device’s lens and the 

subject’s eye must be at least 100 millimeters. In order to provide an acceptable level of 

usability and ease of alignment, the camera must allow for some variability in the position 

of the iris center relative to the camera. The 2015 Update to the ANSI/NIST-ITL standard 

is consistent with ISO/IEC 19794-6 and ISO/IEC 29794-6 specifications concerning image 

 

33 Note that this corresponds to ISO/IEC 19794-6 specifications as well as the 2015 Update of the ANSI/NIST-ITL standard. 

ISO/IEC 29794-6 specified 15.7 pixels / mm. which is allowed with IAP levels 30 and 40. 

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margin requirements. The vertical margin shall be > 0.2 times the radius of the iris. The 

horizontal margin shall be > 0.6 times the iris radius. See Figure 7. 

Figure 7 

Image Margin Requirements

9.3 Iris Image Transmission

In order to support interoperability, the Mobile ID iris image capture device shall support 

ANSI/NIST-ITL Update: 2015 type-17 records when communicating with a central system. 

However, as indicated in Table 11 and Figure 8, alternate configurations are possible 

without having to fully encode an ANSI/NIST-ITL transaction at the mobile unit level. 

For Mobile applications, it is often best to use the Image Storage Format (ISF) 7 format, since 

it dramatically reduces the storage requirements for the eye, as well as the data transmission 

load. For stationary systems, ISF 2 is the most common option deployed. Note that cropping 

and masking in ISF 7 does not affect the ability of the iris matching system to accurately 

perform. 

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Table 11

Iris Storage Formats (ISF)

ISF Code Description Iris Centering

Iris Margin Requirement

(R is radius of the iris)

Horizontal Vertical

1 Unconstrained 

image size Recommended > 0.6 R > 0.2 R

2 Raw: 640 x 480 Recommended > 0.6 R > 0.2 R

3 Cropped Required = 0.6 R = 0.2 R

7 Cropped and 

Masked Required = 0.6 R = 0.2 R

Figure 8 

Examples of ISF image formats from the ANSI/NIST-ITL standard

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10 Voice Signals

Voice signals are by their nature something that must be captured over a period of time. 

The voice signals may be used as input to multiple processes, once captured, such as:

• Speech processing (recognizing the words spoken)

• Language and dialect identification

• Speaker verification and identification (a biometric application)

• Counting the number of participants in a conversation

Voice sounds can carry speech and that speech usually occurs within a social context 

involving more than one speaker. The human voice – generally carrying both speech and 

non-speech sounds – propagates varying distances through air (principally) or another 

medium to reach acoustic transducers (usually microphones, when recorded) of varying 

amplitude and phase response. In mobile applications, even a single segment of a voice 

signal may not be linkable to a single geographic location or to a specific speaker. Unlike 

other modalities, voice signals may reflect and depend upon the social and behavioral 

conditions -- as well as the environmental condition of the collection environment, 

including the relationship between the data subject and any interlocutors. 

10.1 Voice Signal Capture Devices

Many hand-held devices, such as phones, now also include the capability to take 

photographs and to record voices. The recordings may be in the form of video (also 

including a visual component) or as totally aural recordings. There are no specific 

requirements for audio capture devices. However, the operator’s system should be 

identifiable – through make and model. 

10.2 Voice Signal Capture 

The date of the recording and its duration should be captured at the time of the recording. 

If possible, geographic location(s) should also be captured. The container format 

encapsulates the audio data of the electronic file used to carry the voice data in a digital 

recording. At the time of capture and initial storage, the container code shall be noted. 

Files having container formats incorporate audio specifications to properly decode the 

audio, such as number of channels, sampling rate, bit/byte depth, and whether the data

is big/little endian. Table 12 lists the most common container formats. If the container 

format is not shown in the table, then code 2 is selected and entered in container code / 

CONC of Field 11.013 (Container / CONT). Field 11.051 (Comment / COM) shall be used 

to describe the container.

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Table 12

Container Codes

*Any mention of commercial products within NIST web pages is for information only; it does not imply recommendation or endorsement by NIST

If the container allows different CODECs to be used, then Field 11.014 (CODEC / CDC) shall 

be completed with the code for the CODEC used to store the recording. The common 

CODECs are shown in Table 13. 

Table 13

 CODEC Codes

Container type Common file 

extension(s)

Container 

code

RAW audio type undefined 0 

Container type reference various 1 

Other various 2 

WAV (RIFF audio) .wav 3 

3GP and 3G2 mobile video .3gp .3g2 4 

AIFF .aiff .aif 5 

MP3 (MPEG-1, Layer 3 audioi) .mp3 6 

NIST Sphere .sph 7 

QuickTime (Apple VBR – audio/video/image) 

Note: allows pointers to external files and 

servers

.mov .gt 8 

Video for Windows .avi 9 

Vorbis (OGG audio) .ogg 10

Windows Media Type 1 .wmv .wma 11

Windows Media Type 2 Note: allows pointers 

to external files and servers

.asf .asx 12

Codec type Codec code

Linear PCM 0 

Codec type reference 1 

Other 2 

Floating –point PCM 3 

ITU-T G.711 (PCM) μ-law with forward order digital samples 4 

ITU-T G.711 (PCM) μ-law with reverse order digital samples 5 

ITU-T G.711 (PCM) A-law with forward order digital samples 6 

ITU-T G.711 (PCM) A-law with reverse order digital samples 7 

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Note that the Container and the CODEC (if specified) should be captured directly by the 

voice recorder and should not require manual intervention on the part of the operator. 

It is recognized that mobile phones, ‘pen recorders’ and other devices may not convey 

such information with a voice recording. In such cases, ‘Other’ may be specified.

Although the standard allows for redaction (overwriting of a portion of the recording), 

discontinuities, specification of vocal content, and other characteristics of the voice 

sample, these should not be entered by the operator in the field. They are best entered 

by analysts reviewing the recording later. 

10.3 Voice Signal Transmission

The type-11 record of ANSI/NIST-ITL shall be used to transmit an audio recording to a 

central repository. However, as illustrated in Figure 4, the full ANSI/NIST-ITL transmission 

file need not be generated at the mobile unit level. 

11 Multiple Modalities in a Single Unit

A mobile ID unit may combine the capability to capture multiple different modalities, and 

several instances of each particular modality. This can greatly increase efficiency and 

improve the possibility of a later match (if an enrollment is being performed). 

A major concern is that the entire sample set from one particular individual must be 

properly linked. This becomes problematic if the capture protocol is such that the process 

of collecting all modalities from a single individual is interspersed with data entries for 

other individuals. Simple typographical mistakes in entering a reference index (or name) 

could cause a lack of cross-linkage, or could cause items to be linked (falsely) together for 

different individuals. There is less chance of this happening when samples are collected 

simultaneously or quasi-simultaneously (such as a facial image taken at the same time as 

iris images). 

The capture devices shall meet all of the characteristics for each of the modalities 

incorporated into them. The operation shall follow best practices for each of the 

individual modalities captured during a particular session. The unit should be capable of 

associating all of the individual samples captured from a single individual together (e.g. 

some common identifier for the fingerprint, the iris image, and the facial photo). This, 

however, may not be possible with certain mobile devices, such as certain smartphones.

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12 Mobile ID Use Cases

The Department of Homeland Security, Office of Science and Technology held a series of 

workshops concerning mobile ID devices. One of their first tasks was to define use cases. 

They identified four general use cases:

Level 0: Credential dependent – no communications

 Function: Verification

Level 1: On-board biometric storage / matching

 Function: Enrollment, Identification, Verification

Level 2: Central server dependent biometric matching

 Function: Enrollment, Identification, Verification

Level 3: Local server dependent communications

Function: Enrollment, Identification, Verification

The participants in the DHS workshops evaluated the following scenarios in order to 

develop the four generalized use cases described above. It is possible for a scenario

to be at any of the above Use Case levels, depending upon the particular environment. 

• Patrol Stop

• Border / Ports of Entry 

• Public Events

• Access Control

• Disaster / Emergency Management

• Maritime

• Post-mortem identification

• Checkpoint operations

• Detention / Asylum Facility Operations 

• County / local jail booking, transfer & release 

• Latent friction ridge print image capture and search from the field 

13 Risk Profiles 

‘Risk’ here refers to the possible implications of having a false match or a false non-match. 

The implications of such ‘errors’ can vary substantially. For purposes of this document, 

they are divided into three levels: Severe, Moderate and Mild. Use cases defined by risk 

are shown in the following Table.

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Table 14

Use cases for risks and functions

Risk to Public 

Safety/Function

Use Case Example Recommended Capture

Severe / Enrollment Field enrollment of biometric data

from an individual that is 

associated with an attempted 

terrorism incident.

Face = Frontal 34

Iris = L&R eyes

Finger = All 

Severe/

Identification

One-to-many search against a 

database to identify a subject 

where there is a high risk of loss of 

life or assets. Some situations may 

require a multi-modal biometric 

identification.

Face = Frontal 34

Iris = L&R eyes

Finger = 4+ 

Severe/

Verification

1:1 match against a credential or 

database to verify identity where 

there is a high risk of loss of life or 

assets. Some situations may 

require multi-modal biometric 

verification.

Face = Frontal 34

Iris = Either eye

Finger = 2+

Moderate/

Enrollment

Mobile booking: Field citations and 

release when the violation is not 

high enough to ensure 

incarceration until arraignment 

without bail.

Face = Frontal 

Iris = L&R eyes

Finger = 6+

Moderate/

Identification

In field mobile identification of a 

subject with questionable or no 

identification.

Face = Frontal

Iris = Either eye

Finger = 4+

Moderate/

Verification

Personal Identity Verification (PIV) 

Release from custody.

Iris = Either eye

Finger = 2+

Mild/

Enrollment

The intention is for the biometric 

enrollment to be of sufficient 

quality that it shall allow later 

verification (e.g. e-citations). 

Face = Frontal 

Iris = L&R eye

Finger = 4+

Mild

/Identification

Rapid identification in custody prior 

to formal booking. (Typically done 

at the jail intake).

Iris = Either eye

Finger = 2+

Mild/

Verification

(Finger images).

Court 

Appearance/Parole/Workhouse, 

Personal Identity Verification (PIV).

Iris = Either eye

Finger = 1+

Mild/

Verification

(Finger minutiae).

Personal Identity Verification (PIV) 

(using minutiae).

Finger = 2+

Not recommended for use between AFIS.

 

34 For face enrollments, verifications and identification in a severe risk environment, attempts should be made to control, background expression 

and lighting where it is practical to do so.

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13.1 Severe Risk

Severe risk levels imply that loss of life and/or property can result if accurate identification 

or verification is not made. In severe risk environments, it is plausible that inconvenience 

to the subject being identified or verified is secondary to the security of the situation, 

meaning subjects may be detained longer until the identification or verification process 

is completed. This assumption means that matching thresholds can be set lower (more 

aggressively) resulting in a returned list of potential candidates that an examiner may 

review to determine if a true match has occurred. 

For instance, with friction ridge prints, it may be deemed prudent to have a forensics 

examiner review the images. A forensics fingerprint examiner can use level 3 fingerprint 

information including inter-ridge detail and pore structure to effect identifications. On 

the other hand, machine matching is typically constrained to level 2 minutiae details and 

ridge spacing. For this reason, fingerprint sensors for enrollment and identification in a 

severe environment must meet EBTS Appendix F35 requirements. In addition, each print 

that can be compared adds information that can be used by the examiner making full tenprint comparisons desirable.

Examples of enrollment and identification functions in a high-risk environment include 

background checks conducted to grant access to secure facilities during battlefield

operations. In this case, enrollment fingerprints would be compared against the latent 

image database maintained by the Department of Defense (DoD). 

The verification function typically compares a processed captured biometric image 

against previously captured templates. Thus, even for verification functions performed 

in a severe risk environment, sensors meeting PIV image quality specifications provide the 

maximum data that will be used for matching. Increased confidence for verification 

functions can be met using multi-instance (e.g. 2 or more fingers) or multi-modal 

biometric verification. 

13.2 Moderate Risk

A moderate risk environment is defined for those encounters with a subject with no or 

questionable identification. An officer cannot detain a subject for more than a limited 

amount of time without making an arrest. In this situation, it is necessary to quickly 

identify the subject or retain biometric information sufficient to verify the subject’s 

identity at a later date. 

For instance, in scenarios relying upon fingerprint matching, PIV image quality enables 

machine matching of images. Once the subject is in the court system, any images retained 

using mobile enrollment would typically be replaced by images captured using a ten-print 

 

35 Appendix F of the FBI’s EBTS us available through the website https://www.fbibiospecs.cjis.gov 

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system. Once again, the capture of more images provides more information for later 

booking. In addition, the capture of two or more fingerprints simultaneously provides 

additional information on the fingerprint sequence. 

13.3 Mild Risk

A mild risk environment is defined for those encounters where enrollment and 

identification data will be used at a later date. At that time, the subject would be available 

for comparison to the data previously retained. The results of an identification or 

verification should not impact anyone but the subject in question. Examples of normal 

enrollments include preparing for future logical or physical access control for a subject, 

or retaining one or more biometric images for verification in court while the subject is 

available. Verification examples include tracking a subject through the jail or court system 

using the retained biometric images. In these cases, a failure to match would result in 

additional action to verify the subject’s identity, primarily inconveniencing no one but the 

subject.

14 Mobile Device Security & Encryption

The establishment and enforcement of Information Technology (IT) and agency security 

policies is not the focus of this document. Law enforcement and criminal justice agencies 

are increasingly realizing the productivity benefits of mobile handheld devices. Mobile ID 

devices represent a tremendous productivity advantage for criminal justice and ID 

management. 

While this mobile technology and the capabilities it brings, from biometric identification 

to citations and report writing, will be a great advantage to criminal justice personnel, it 

is creating a tremendous security management challenge. The small size, large storage 

capacity and network connectivity of these devices make unprotected mobile devices 

susceptible to loss, theft and misuse, and possibly a target for someone wanting 

unauthorized access to information or databases. Mission sensitive and confidential 

information is now available through Mobile ID devices at locations and under 

circumstances that are outside the normal security parameters. As a result, unsecured 

devices can pose a risk to any criminal justice network that the device can access. In order 

to adequately secure the device from misuse or attack and to meet regulatory standards 

and requirements, agencies must develop wireless and centralized device security 

policies. These policies should include measures regarding authentication, data 

expungement, encryption, application launch controls and device feature disablement.

In order to maintain the highest level of device security, an updating of all devices is 

needed whenever policies change or software is updated to provide greater protections. 

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14.1 Authentication and Authorization

The mobile handheld device should provide the capability for an operator to authenticate 

his/her identity as well as establishing authorization levelsfor that person based on a twofactor authentication, one of which should be a biometric. 

The mobile handheld device should provide biometric operator authentication and a 

password of minimum length with alphabetical/numeric/special characters. For certain 

Government operations, a PIV card may be able to provide operator authentication, if the 

operator has been issued one. 

The mobile handheld device should provide the capability for operator re-authentication 

and the device should re-authenticate itself after a designated amount of idle time or 

result in a device shut-off. The mobile handheld device should provide the capability to 

lock the device or render the device inoperable, erase selective files, and/or erase all files 

on the device based on failed security protocols. The mobile handheld device should 

provide the capability to establish a maximum limit of failed authentication attempts 

before the handheld clears all application data or requires unlock only by an IT 

administrator.

14.2 Device and Data Authentication 

Once operator authentication and authorization is established, the mobile handheld 

device should be able to provide device authentication that it is authorized to 

communicate on the network. There should also be the capability to have the device’s 

identification verified against a registered list of specified devices (black list, lost/stolen). 

A device with a matching identification to one on the list should not be authorized to 

communicate with the central system. The device should have a remote data ‘wiping’ 

capability in the event that it is misplaced or stolen.

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15 Communication Protocols

There are several different approaches for establishing communication between Mobile 

ID devices and systems. As an example, Figures 9 and 10 illustrate different configurations 

using the Web Services –Biometric Devices protocol.

Figure 9 

A physically separated WS-Biometric Devices (WS-BD) implementation.

Figure 10

A physically integrated WS-Biometric Devices (WS-BD) implementation

The type of communications selected will vary upon the needs of the mobile ID user. 

Some scenarios, such as maritime interdiction, may require satellite communications 

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while others can use the commercially available mobile phone network. The 

communications between components can be of many different types,such as Bluetooth. 

16 Environmental Profiles

A Mobile ID device can be used in a variety of different contexts, such as a court of law, 

an airport terminal, by a patrol officer on the street or in a patrol car, or even in a military 

environment such as a checkpoint or for access control to a military base.

These different contexts each require different levels of resistance to environmental 

factors such as temperature, humidity, dust, water, vibration, etc. For these reasons, 

three different profiles are described below (Indoor, Law Enforcement and Military), with 

increasing levels of resistance to the relevant environmental conditions.

It is the responsibility of the agency to decide, in the procurement phase of the Mobile ID 

devices, which profile to request in the Request for Proposal (RFP). The desired profile

will depend on the expected usage of the devices and the location(s) where they will be 

required to operate. It is important to choose the right profile, since a lower profile could 

mean that the devices are not able to withstand the operating environment, causing 

costly failures and decreasing service levels. Conversely, choosing too high a profile is 

likely to cause an unnecessary increase in the size, weight and cost of the devices.

16.1 Indoor Profile

If a Mobile ID device is going to be used only in an environment such as an office building, 

a court of law, etc. the suggested environmental specifications for the device can be 

assumed to be similar to those of most commercially available computing devices 

intended for office use. For these use cases, the recommended minimum environmental 

specifications are listed in Table 15. 

Table 15

Indoor Profile Recommendations

Operating temperatures From 32°F to 104°F (0°C to 40°C)

Storage temperatures From 14°F to 122°F (-10°C to 50°C)

Relative humidity 0% - 85% 

Non-condensing

Ingress Protection Rating (IP Code) IP 40 or higher

For more information about the level of ingress protection (IP) refer to the IEC 

standard 60529 “Degrees of protection provided by enclosures” available at 

http://webstore.ansi.org. 

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16.2 Outdoor – Heavy Use (Law Enforcement – like) Profile

This profile should be used when the Mobile ID devices are going to be used by a 

patrol officer on the street or on-board a patrol car, for example. These use cases 

require the devices to be able to withstand high or low operating temperatures, dust, 

rain, water splashes, the vibrations typically encountered in a vehicle and dropped

from a limited height. For these use cases, the recommended minimum 

environmental specifications are listed in Table . 

Table 16

Law Enforcement Profile Recommendations

Operating temperatures From 14°F to 122°F (-10°C to 50°C)

Storage temperatures From -4°F to 140° F (-20°C to 60°C)

Relative humidity 10% - 90% non condensing

Ingress Protection Rating 

(IP Code)

IP 54 or higher, in operational configuration, with any 

existing expansion port closed

Drop resistance Resistance to multiple drops on concrete from a 

height of 3 feet (91 cm). 

16.3 Outdoor – Rugged Use (Military – like) Profile

This profile should be used when the Mobile ID devices are going to be used in harsh 

operating environments, when the expected use cases require the devices to provide 

increased level of protection against high and low temperatures, dust and sand, rain, water 

splashes, vibrations and drop. The Department of Defense has issued a document that should 

be followed for testing to this profile. It is “Department of Defense Test Method Standard: 

Environmental Engineering Considerations and Laboratory Tests, Mil-Std-810G” which is

dated 1 January 2010. The document is available at 

http://www.atec.army.mil/publications/Mil-Std-810G/Mil-Std-810G.pdf. Particular 

attention should be paid to the tests for operating temperatures, storage temperatures, drop 

resistance, vibration resistance, and relative humidity tests. The ingress protection (IP) 

should be code IP 65 or higher, with any existing expansion port closed. 

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Annex A Revision History

Revision Number Comment

2.0 Initial version.

2.1 Reverted IAP 20, 30, and 40 to original conditions, added IAP 10, 11, 12. Made 

minor modification to guidance on the wearing of glasses during face image 

captures and SMT image capture requirements.

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This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.SP.500-280v2.1