OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

1

OSAC 2022-S-0007

Standard Guide for Facial 

Comparison: Overview and 

Methodology Guidelines

Facial Identification Subcommittee

Digital/Multimedia Scientific Area Committee

Organization of Scientific Area Committees (OSAC) for Forensic Science
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

2

OSAC Proposed Standard

OSAC 2022-S-0007

Standard Guide for Facial

Comparison: Overview and 

Methodology Guidelines

Prepared by 

Facial Identification Subcommittee

Version: 2.0

October 2022

Disclaimer:

This OSAC Proposed Standard was written by the Facial Identification Subcommittee of the Organization 

of Scientific Area Committees (OSAC) for Forensic Science following a process that includes an open 

comment period. This Proposed Standard will be submitted to a standards developing organization and is 

subject to change.

There may be references in an OSAC Proposed Standard to other publications under development by 

OSAC. The information in the Proposed Standard, and underlying concepts and methodologies, may be 

used by the forensic-science community before the completion of such companion publications.

Any identification of commercial equipment, instruments, or materials in the Proposed Standard is not a 

recommendation or endorsement by the U.S. Government and does not imply that the equipment, 

instruments, or materials are necessarily the best available for the purpose.

To be placed on the OSAC Registry, certain types of standards first must be reviewed by a Scientific and 

Technical Review Panel (STRP). The STRP process is vital to OSAC’s mission of generating and 

recognizing scientifically sound standards for producing and interpreting forensic science results. The 

STRP shall provide critical and knowledgeable reviews of draft standards or of proposed revisions of 

standards previously published by standards developing organizations (SDOs) to ensure that the 

published methods that practitioners employ are scientifically valid, and the resulting claims are 

trustworthy.

The STRP panel will consist of an independent and diverse panel, including subject matter experts, 

human factors scientists, quality assurance personnel, and legal experts, which will be tasked with 

evaluating the proposed standard based on a comprehensive list of science-based criteria.

For more information about this important process, please visit our website 

at: https://www.nist.gov/topics/organization-scientific-area-committees-forensic-science/scientifictechnical-review-panels. 
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

3

Standard Guide for Facial Comparison:

Overview and Methodology Guidelines

1. Scope

1.1 The purpose of this document is to provide a general overview of facial comparison 

applications, categories, and methods. It provides guidelines and recommendations for 

conducting manual facial comparisons, in support of the four identified facial comparison 

applications. 

1.2 This document does not address specific standard operating procedures for conducting facial 

comparisons, nor does it address specific training, documentation, or reporting requirements. 

1.3 This document does not address the use of facial recognition algorithms. 

1.4 This standard does not purport to address all of the safety concerns, if any, associated with 

its use. It is the responsibility of the user of this standard to establish appropriate safety and 

health practices and determine the applicability of regulatory limitations prior to use.

1.5 This standard cannot replace knowledge, skill, or ability acquired through appropriate 

education, training, and experience and should be used in conjunction with sound professional 

judgment.

2. Referenced Documents

2.1 ASTM Standards:

E2916 Terminology for Digital and Multimedia Evidence Examination

E3149 Standard Guide for Facial Image Comparison Feature List for Morphological

Analysis

E3115 Standard Guide for Capturing Facial Images for Use with Facial Recognition

Systems

[OSAC Overview of ACE-V Document Placeholder]

3. Terminology

3.1 Definitions:

3.1.1 E2916 Standard Terminology for Digital and Multimedia Evidence Examination 

3.1.2 Forensic, n— refers to an application of facial comparison in which comparisons are 

conducted to provide information in the form of testimony in court.
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

4

3.1.3 Identity verification, n—The process of assessing whether a person and an image

represent the same individual or whether two or more images represent the same individual.

3.1.4 Opinion, n—View, judgement, belief - takes into consideration other information in 

addition to observations, data, calculations, and interpretations.

3.2 Acronyms:

3.2.1 OSAC, n – Organization of Scientific Area Committees for Forensic Science

3.2.2 ACE-V, n – Analysis, Comparison, Evaluation, and Verification

4. Summary of Guide

4.1 This guide identifies and defines the four main applications of facial comparison, the three 

categories of facial comparison, and three methods of conducting facial comparisons. This guide 

recommends practitioners use morphological analysis as the primary facial comparison method 

for all applications and categories of manual facial comparison. Morphological analysis is the 

industry-wide accepted method based on the collective experience of facial comparison 

practitioners. 

5. Significance and Use

5.1 Apart from the methods described below, humans have an innate ability to recognize faces. 

This ability is more accurate when comparing familiar faces versus unfamiliar faces and is referred 

to as holistic comparison (Biederman & Kalocsai, 1997; Maurer, Le Grand, & Mondloch, 2002; 

Rossion, 2008). Holistic comparison is not recognized as a method of facial comparison by the 

Facial Identification community. People have a wide range of abilities when comparing faces. 

Some have limited abilities (commonly referred to as "face blind") whereas others have unique

innate abilities (sometimes referred to as "super recognizers"). Super-recognizers have superior 

ability to recognize unfamiliar faces than the general population and are equally as accurate as 

trained facial examiners or facial reviewers when conducting facial comparisons of unfamiliar 

faces (Philips et al., 2018).

5.2 Facial comparison is a manual process conducted by a human which entails identifying 

similarities and differences between two images or an image and a live subject to determine 

whether they represent the same person. Practitioners conduct facial comparisons to support 

different applications for the purpose of identity verification. The application, purpose, and 
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

5

resources available for a facial comparison task determine which category of facial comparison 

should be conducted. 

5.2.1 The following four applications describe functional areas where facial comparisons are 

conducted to support identity verification. Most facial comparisons fall primarily into one of 

the following four applications, however crossover may exist.

5.2.1.1 Intelligence Gathering for Identity Management: Facial comparisons are 

conducted to support the compilation of information relating to what is believed to be a single 

subject, even if the identity of the subject is not known.

5.2.1.2 Screening and Access Control: Facial comparisons of both image-to-image and 

image-to-person are conducted in a high throughput environment and are thus limited in time 

(e.g., customs and immigration checkpoints).

5.2.1.3 Investigative and Operational Leads: Facial comparisons provide information to 

assist operational personnel with meeting their objective (e.g., comparing an unknown subject 

featured in one or many images to images of known subjects to provide investigators with a 

potential name for a crime suspect).

5.2.1.4 Forensic: Facial comparisons are conducted to provide information to support

testimony in court. 

5.3 There are three broad categories of facial comparison: assessment, review, and examination.

5.3.1 Assessment is a quick comparison of image-to-image or image-to-person, typically 

conducted in screening and access control applications, and often in real time. Due to time and 

resource constraints, assessment is the least rigorous of all the facial comparison categories

and is often not documented. 

5.3.2 Review is a comparison of image(s)-to-image(s) often used in either investigative and 

operational leads or intelligence gathering applications. A broad range of purposes and levels 

of rigor are involved in review, though it is by nature more rigorous than the assessment 

process and may require some level of documentation.

5.3.3 Examination is a comparison of image(s)-to-image(s) often used in a forensic 

application. Examination is the most rigorous category of facial comparison and typically 

requires more detailed documentation. 
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

6

5.3.4 Detailed descriptions of, and distinctions between, the three categories of facial 

comparison are beyond the scope of this standard guide. 

6. Comparison Methods and Guidelines

6.1 There are three facial comparison methods currently identified in the facial identification 

community: morphological analysis, superimposition, and photo-anthropometry. 

6.2 Morphological analysis should be the primary approach used for facial comparison in all 

categories: assessment, review, and examination. 

6.2.1 Morphological analysis is the method of facial comparison in which the features and 

components of the face are compared. Morphological analysis is based on the evaluation of the 

correspondence among facial features (components), component characteristics, and their 

respective characteristic descriptors (e.g., presence, shape, appearance, symmetry, location, 

relative proportion). Features include those corresponding to the overall face, facial 

components (e.g., nose, ear, mouth), their component characteristics (e.g., nostrils, ear lobes, 

helix), and discriminating characteristics, such as scars, marks, and tattoos. The E3149

“Standard Guide for Facial Image Comparison Feature List for Morphological Analysis” 

provides a standard list of facial components and component characteristics to be assessed and 

evaluated during a morphological analysis. Research shows that morphological analysis is 

highly accurate and reliable when comparing controlled facial images to non-controlled facial 

images (Bacci et al., 2021). 

6.2.2 The morphological analysis process should not rely on classification schemes (e.g., 

round face, Roman nose), which result in interobserver differences and are, therefore, not best 

practice (Iscan, 1993; Penry, 1971; Ritz-Timme et al., 2010; Vanezis et al., 1996). 

6.2.3 Documentation of a morphological analysis is best practice, but the amount of detail 

will vary depending on agency procedures and the application or category of the comparison. 

6.2.4 Morphological analysis is highly dependent on the quality and quantity of the facial 

features and characteristics that can be compared, which is in turn dependent on the capture 

conditions and quality of the image. Image quality can be affected by several factors, including 

but not limited to image resolution, lighting, focus, pose, angle, orientation, or obstructions of 

facial features. 
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

7

6.2.5 The morphological analysis method requires training consistent with the category of the

comparison conducted. Specific training requirements for each facial comparison category will 

be addressed in a forthcoming standard guide. 

6.3 Superimposition should be used only to aid in the facial comparison process and shall never 

be used as a stand-alone approach within any category: assessment, review, or examination.

6.3.1 Superimposition is the process of creating an overlay of two aligned images and 

comparing them visually. 

6.3.2 Superimposition should be applied only when two images are taken from the same 

viewpoint (images may be photographs, frames or images from video, or images synthesized 

from 3D face or head models). Images should be aligned (e.g., scaled, rotated, etc.) with each 

other. There should be a concordance between images in all aspects of angle and perspective 

to avoid distortion of the spatial distribution of facial features and characteristics. Practitioners 

should only use tools which preserve shapes and should not use image processing techniques 

which may skew the images, facial proportions, or shapes. 

6.3.3 Since superimposition is sensitive to image quality, both images should be captured 

under optimal conditions (as defined by E3115) or the use of this method may be misleading. 

Loss of image quality through blurring, compression artifacts, reduction in spatial resolution 

(e.g., number of pixels between the pupils), lens distortion, perspective distortion, etc. reduces 

the ability to determine the specific location of individual features, which subsequently reduces 

the ability to generate an accurate overlay/superimposition. 

6.3.4 In cases where there are multiple copies of the same original image (e.g., forged identity 

documents), superimposition may be conducted on images displaying less than optimal quality

as the images are proportionally the same.

6.4 Photo-anthropometry shall not be used to support any of the identified applications of facial 

comparison in any category: assessment, review, or examination. Photo-anthropometry may be 

used in other applications not covered in this guide, such as research. 

6.4.1 Photo-anthropometry is the measurement of dimensions and angles of anthropological 

landmarks and other facial features visible in an image in order to quantify characteristics and 

proportions. The measurements taken from one image are compared to the measurements taken 

from a separate facial image. 
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

8

6.4.2 As in superimposition, photo-anthropometry is highly sensitive to image capture and 

quality factors including but not limited to resolution, focus, distortion, obscuration, viewpoint, 

lighting, and pose. In addition, the following information should be known about the images 

prior to conducting the comparison: focal length, lens distortion and subject distance. Photoanthropometry should only be conducted when the image capture and quality factors of the 

images being compared are controlled and are the same. Given the uncontrolled conditions 

under which many questioned images (e.g., security camera images) are captured, it is often 

not possible to conduct a proper photo-anthropometric comparison. 

6.4.3 Research on the use of anthropometric comparison has shown that photoanthropometry does not produce consistent results and may be misleading (Kleinberg, 2007; 

Moreton and Morley, 2011). 

6.5 Analysis, Comparison, Evaluation, and Verification (referred to as ACE-V) is the scientific 

process implemented by facial comparison practitioners. Depending on the application and 

category of the comparison, agency procedures may include some or all of the ACE-V steps. 

6.5.1 Analysis refers to the assessment of an image to determine suitability for comparison, 

including the ability to discriminate significant features.

6.5.2 Comparison refers to the examination of two or more samples to establish similarities 

and dissimilarities. The facial comparison methods recommended above (morphological 

analysis and superimposition) should be used during the comparison step of ACE-V.

6.5.3 Evaluation refers to the assessment of the value of details observed during the analysis 

and comparison steps to reach an opinion.

6.5.4 Verification refers to the review or independent analysis of the opinion of another 

examiner. Verification rarely occurs in facial assessment, may be conducted in facial review, 

and should be conducted facial examination. The use of the verification step is dependent on 

agency procedures and time or resource constraints. 

7. Summary of Recommendations

7.1 Morphological analysis method is the best practice for facial comparison, based on the 

collective knowledge and experience of practitioners in the facial comparison community. When 
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

9

conducting morphological analysis for facial comparison, and the application warrants, the 

examination and decision-making process should be fully documented. 

7.2 Superimposition should only be used in conjunction with morphological analysis. 

7.3 Photo-anthropometry shall not be used for facial image comparison.

REFERENCES

Bacci, N., Davimes, J., Steyn, M. & Briers, N. (2021). Forensic Facial Comparison: Current 

Status, Limitations, and Future Directions. Biology. 10. 1-26. 10.3390/biology10121269.

Biederman, I., & Kalocsai, P. (1997). Neurocomputational bases of object and face recognition. 

Philosophical Transactions of the Royal Society B: Biological Sciences 352(1358), 1203-1219.

Bruce, V., Henderson, Z., Greenwood, K., Hancock, P., Burton, A., Miller, P., Verification of 

face identities from images captured on video, Journal of Experimental Psychology: Applied, 5, 

339-360, 1999. 

Bruce, V., Henderson, Z., Newman, C., Burton, A. M., Matching identities of familiar and 

unfamiliar faces caught on CCTV images, Journal of Experimental Psychology: Applied, 7, 

207-218, 2001. 

Burton, A. M., Wilson, S., Cowan, M., Bruce, V., Face recognition in poor-quality video: 

evidence from security surveillance, Psychological Science, 10, 243-248, 1999. 

Butavicius, M., Mount, C., MacLeod, V., Vast, R., Graves, I., Sunde, J., An experiment on 

human face recognition performance for access control, Knowledge-Based Intelligent 

Information and Engineering Systems, 12th International Conference KES, 141-148, 2008. 

Edmond, G., Biber, K., Kemp, R., Porter, G., Law's looking glass: expert identification 

evidence derived from photographic and video images, Current Issues in Criminal Justice, 20, 

337-377, 2009. 

Evison, M., Dryden, I., Fieller, N., Mallett, X., Morecroft, L., Schofield, D., Vorder Bruegge, 

R., Key parameters of face shape variation in 3D in a large sample, Journal of Forensic Science, 

55, 159-162, 2010.

Henderson, Z., Bruce, V., & Burton, A. M., Matching the faces of robbers captured on video, 

Applied Cognitive Psychology, 15, 445-464, 2001. 

Hill, H. and Bruce, V, Effects of lighting on matching facial surfaces, Journal of Experimental 

Psychology: Human Perception and Performance, 22, 986-1004, 1996. 

Iscan, M.Y. and Helmer, R.P. (ed.), Forensic analysis of the skull: craniofacial analysis, 

reconstruction, and identification, Wiley-Liss, 57-70, 1993.

Kemp, R., Towell, N., Pike, G., When seeing should not be believing: photographs, credit cards 

and fraud, Applied Cognitive Psychology, 11, 211-222, 1997. 

Kleinberg, K.F., Vanezis, P., Burton, A.M., Failure of anthropometry as a facial identification 

technique using high-quality photographs, Journal of Forensic Science, 52, 779-783, 2007.
OSAC 2022-S-0007 Standard Guide for Facial

Comparison: Overview and Methodology Guidelines

10

Lee, W.J., Wilkinson, C.M., Memon, A., Houston, K., Matching unfamiliar faces from poor 

quality closed-circuit television (CCTV) footage: an evaluation of the effect of training on facial 

identification ability, AXIS, 1, 1, 19-28, 2009. 

Maurer, D., Le Grand, R., & Mondloch, C. J. (2002). The many faces of configural processing. 

Trends in Cognitive Sciences, 6(6).

Megreya, A.M. and Burton, A.M., Unfamiliar faces are not faces: evidence from a matching 

task, Memory & Cognition, 34, 865-876, 2006. 

Moreton, R. and Morley, J., Investigation into the use of photoanthropometry in facial image 

comparison. Forensic Science International, 212, 231-237, 2011.

Phillips, P., Yates, A., Hu, Y., Hahn, C., Noyes, E., Jackson K., Cavazos, J., Jeckeln, G.,

Ranjan, R., Sankaranarayanan, S., Chen, J., Castillo, C., Chellappa, R., White, D., O’Toole, A.,

Face recognition accuracy of forensic examiners, superrecognizers, and face recognition 

algorithms,” Proceedings of the National Academy of Sciences, vol. 115, no. 24, pp. 6171–

6176, 2018.

Penry, J., Looking at faces and remembering them: a guide to facial identification, Elek, 1971.

Rossion, B. (2008). Picture-plane inversion leads to qualitative changes of face perception. Acta 

Psychologica, 128(2), 274-289.

Ritz-Timme, S., Gabriel, P., Obertovà, Z., Boguslawski, M., Mayer, F., Drabik, A., Poppa, P., 

De Angelis, D., Ciaffi, R., Zanotti, B., Gibelli, D., Cattaneo, C., A new atlas for the evaluation 

of facial features: advantages, limits, and applicability, International Journal of Legal Medicine, 

125, 2, 301-306, 2010.

Towler, A., White, D., & Kemp, R. I. (2017). Evaluating the feature comparison strategy for 

forensic face identification. Journal of Experimental Psychology: Applied, 23(1), 47-58. 

doi:http://dx.doi.org/10.1037/xap0000108.

Vanezis, P., Lu, D., Cockburn, J., Gonzalez, A., McCombe, G., Trujillo, O., Vanezis M., 

Morphological classification of facial features in adult caucasian males based on an assessment 

of photographs of 50 subjects, Journal of Forensic Sciences, 41, 786-791, 1996.