SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 1 of 64

November 16, 2011

SWGFAST Response to

The Research, Development, Testing & Evaluation

Inter-Agency Working Group of the

National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Preamble: This report aims to provide a consolidated list of annotated bibliographic references of 

published research related to latent print analysis in response questions forward by the 

Research Development Testing & Evaluation Interagency Working Group (RDT&E IWG) in 

their letter to the chair of SWGFAST dated September 9, 2011.

This group reply has been prepared by a dedicated task force established at the University 

of Lausanne (forensic science department of the Faculty of law and criminal justice) under 

the direction of Professor Christophe Champod. It was composed of academic staff, 

researchers and last year MSc students in forensic science. The Lausanne team was 

composed of: Alexandre Anthonioz, Lea Bassil, Andy Becue, Christophe Champod, 

Nicolas Crettaz, Nicole Egli, Marcela Espinoza, Maya El-Charbaji, Merwan El‟Khoury, 

Thomas Fitzi, Éloïse Forest-Allard, Aline Girod, Laetitia Maddalena, Sébastien Moret, 

Marieve Rocque, Céline Schürch, Sabrina Wenger.

A core group of SWGFAST members including: Lenny Butt, Christophe Champod, Melissa 

Gische, Scott Hecker, Glenn Langenburg, Alice Maceo and Maria Roberts served as 

editorial advisors to the task force.

The report was circulated for review by all SWGFAST members.

This report will not provide an exhaustive list of references that can be found in relation to 

friction ridge skin impressions and their examination, but will focus on key scientific 

published papers that address, to some degree, the questions raised by the RDT&E IWG. 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 2 of 64

November 16, 2011

Papers providing examples, case studies or anecdotal evidence have not been considered. 

The selected papers often provide reviews and also a set of references that constitute 

material for further reading.

This report is structured following the list of questions put together by RDT&E IWG in a 

column format: the left column recalls the questions put forward by the working group and 

the right column gives the consolidated and annotated bibliography.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 3 of 64

November 16, 2011

1.1. Underlying Fingerprint Characteristics

1.1.1. What scientific literature describes 

how distinct or similar fingerprints 

are across:

● The overall population? 

● Related individuals?

● Identical twins?

We suggest that we break down according to levels of features:

Level 1 features:

(1) In the general population:

[Mavalwala, J., 1977]

The book provides an extensive bibliography on the subject of dermatoglyphics, including over 

3000 references. It covers all areas where dermatoglyphics are used except identification work 

as used by law enforcement agencies. The time frame spans the end of the 19th century and 

concludes in 1973. It is an extremely valuable resource for research dealing with the 

distribution of level 1 features (essentially classes of general pattern and metrics of ridge 

counts) on both fingers and palms in a range of populations (small tribes to large ethnic 

groups).

[Kumbnani, H. K., Anthropology Today: Trends, Scope and Applications, 2007]

This article offers an etymological review of dermatoglyphics which shows the valuable 

implications, applications and utility of the work carried out in this area. It is based on more 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 4 of 64

November 16, 2011

than 220 references covering the years 1891 to 2005. More specifically, the author covers 

published work on the frequency of various patterns for fingerprints in different communities 

and populations. Studies on palm, sole, and toe prints as well as on middle and proximal 

phalanges are covered, showing their strong and weak points. A review of work relating to 

inheritance and to the correlation between dermatoglyphics and diseases is also presented. 

The role of dermatoglyphics for personal identification, disputed paternity, and diagnosis of 

monozygotic (identical) versus dizygotic (fraternal) twins is also reviewed.

(2) Data on level 1 features acquired in the context of law enforcement:

Extensive datasets of fingerprints and palmprints have been acquired by law enforcement 

agencies and classified according to general pattern (using various classification systems - see 

[Hutchins, L. A., The Fingerprint Sourcebook, 2011]). This data is not generally part of the 

public domain (apart from a few generic summaries or data available in the Internet: 

www.dermatoglyphics.com) with one exception in relation to palmprints.

[Tietze, S. and Witthuhn, K., Bka - Polizei + Forschung, 2001]

A large amount of information concerning the general characteristics of palms is given in this 

book based more on experience rather than structured research. However, a large amount of 

statistical data as to the ridge flow in different parts of the palm is presented. This data comes 

from operationally acquired palmprints. Observations are presented by palmar area (interdigital 

area, thenar and hypothenar, left and right hand). As an example of the type of data presented, 

general patterns present in the interdigital area are detailed as to their shape and placement, 

allowing the determination that based upon the observation of classifications of 34375 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 5 of 64

November 16, 2011

interdigital areas between the index and middle finger on right hands, 2138 loops have been 

observed; also, the data reveal that such loop patterns in the interdigital area were more 

frequently observed in right than in left hands, and that among the loop patterns observed in 

the right hand, most are between the middle and the ring finger, followed by the space between 

the ring- and the little finger and finally between the index and middle finger

(3) Specifically among related individuals and twins:

[Loesch, D. Z., Oxford Monographs on Medical Genetics, 1983]

A topological system to describe papillary surfaces is presented. A series of dermatoglyphic 

measurements are associated with this system, such as ridge counts or ridge breadth. The 

system then allows interpreting the relationships between pattern elements and combinations 

thereof. The book is divided into three parts and covers the subjects of the classification of 

dermatoglyphic patterns and their topology, the variability within and between human 

populations of topologically significant pattern elements, their heritability and diagnostic 

application. 

[MacArthur, J. W., Human Biology, 1938]

In order to state the degree of similarity in dermatoglyphic features between individuals and 

between hands and feet of one individual, a quantitative and objective method was developed 

and is presented in this paper. Comparisons were made bilaterally (hands of one person), 

homolaterally (same side hands of pair), and heterolaterally (opposite side hands of pair) 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 6 of 64

November 16, 2011

between parents and children, siblings, mono- and dizygotic twins, and left and right hands of 

individuals. Differences in terms of ridge count, finger pattern, palmar digital and axial triradii, 

and palm patterns were accounted for. Averages and ranges of differences for all pairwise 

comparisons are given and suggest that the method developed has potential in distinguishing 

identical pairs or sets.

[Colletto, G. M. D. D., et al., Brasil. J. Genetics, 1987]

This paper proposes the use of dermatoglyphic analysis to determine twin zygosity. The study 

sample consists of 120 same sex twin pairs, of which 66 are monozygous and 54 are dizygous. 

Numerical values were given to 35 dermatoglyphic variables in order to calculate a 

dermatoglyphic index. A discriminant analysis was then applied to within-pair differences of 

these dermatoglyphics variables. 15 of these variables were selected to be used in a function 

allowing the proper classification of 100% of the twin pairs in this study. Other methodologies 

are recommended for cases in which the probability of mono- or dizygosity is below 90%.

[Steinman, G., The Journal of Reproductive Medicine, 2001]

The author observed 250 fingerprints to examine the role of genetics and environmental factors 

affecting the general pattern of finger prints in uniovular triplets, quadruplets, and quintuplets. 

Results suggest that as the monozygotic set increases, the concordances in finger print pattern 

decreases within the set; twins were shown to have 88% concordance, 84% in triplets, 74% in 

quadruplets and only 71% concordance in quintuplets. These differences may be explained by 

a higher potential for mutation, as well as increased local dissimilarities within the uterine 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 7 of 64

November 16, 2011

environment in larger sets.

[Reed, T., et al., American Journal of Medical Genetics Part A, 2006]

The authors analyzed 2,484 twin-pairs to estimate the genetic and environmental influences on 

the presence of an arch pattern on any fingertip. This estimate is based on the comparison of 

monozygous and dizygous twin pairs. The results of this study agree with previous studies in 

relation to overall frequency of arches (4.3%) and to difference in frequency of arches by sex 

with a higher frequency in females than males (5.5% in females and 3.2% in males). In terms 

of heritability, the results of this study suggest a very high heritability (91%) and therefore 

suggest searching for the genetic locus responsible for the arch pattern. A discussion of 

previous genetics studies and the formation of dermatoglyphic patterns is given in order to 

suggest possible loci to consider.

Level 2 features: see section 1.2 below
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 8 of 64

November 16, 2011

Level 3 features:

[Ashbaugh, D. R., La gazette de la Gendarmerie Royale du Canada, 1983]

Locard and Wilder & Wentworth‟s work on poroscopy is discussed and the author examines 

their findings. It was found that the dimensions of pores are variable between fingerprints but 

relatively similar within fingerprints. Regarding pore shapes, different shapes exist and they 

vary within fingerprints. Pore position, being the most interesting characteristic, was found to 

be misaligned from the center of the ridge at times. Also, pores can be grouped or scattered 

along the ridges depending on the area considered. A statistical explanation to Locard‟s 

recommended 20-40 pores necessary for identification as well as recommendations for 

distorted or missing pores are also given. The author argues that the pores are permanent and 

unchangeable but also variable between prints and that poroscopy is a valid method for 

identification. However, due to pore shape variation in inked prints Ashbaugh suggests 

focusing on the location of pores for comparison.

[Roddy, A. R. and Stosz, J. D., Proceedings of the IEEE, 1997]

This paper explores statistical behavior of pores on fingerprints and how the performance of 

biometric systems can be improved by adding the use of pores to the use of minutiae. The 

model described estimates for the probability of finding a given configuration of pores under 

various conditions among which are the environmental conditions, the matching algorithm 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 9 of 64

November 16, 2011

used, and the resolution of the scanned fingerprint. Analyses carried out in this study indicate 

that the probability of two random people having an identical configuration of pores is 

sufficiently low to avoid a false inclusion even if it exists when using an automated system. 

Parameters such as plasticity and distortion were also considered in order to lower false 

rejects, which in turn, may increase the rate of false accepts.

[Chen, Y. and Jain, A., Advances in Biometrics: Third International Conference, ICB 2009, 

Alghero, 2009]

The authors propose a model to quantitatively measure the rarity of fingerprints which 

incorporates all three levels of fingerprint features and their distribution: fingerprint class 

(general pattern), position and direction of minutiae, ridge period, ridge curvature, and pore 

spacing. For the evaluation and validation of this model the theoretical probability of random 

correspondence was computed and compared to that of empirical values obtained from the 

NIST Special Database 4. Higher probabilities of matching impostor fingerprints are observed 

for same class fingerprints than for different classes, and this probability is reduced, both 

theoretically and empirically, when information on ridge features and pore spacing are 

included.

[Parsons, N. R., et al., Law Probability and Risk, 2008]

The authors suggest using an automatic and quantitative measure of pore configuration to 

supplement expert judgment associated with a match. Inked prints were compared to each 

other using a method of grey-level extraction based on principal components analysis (PCA) of 

a large class of pores. The statistical properties of configurations of the matching pores from 

prints of the same finger are compared to those of prints taken from different fingers. Although 

results from this study indicate that analysis based on configurations of centroids of pores 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 10 of 64

November 16, 2011

works quite well under linear realignment, the authors recommend a large-scale survey.

1.1.2. What scientific literature describes 

the theoretical or biological basis 

for the distinctiveness of 

fingerprint characteristics? 

1.1.3. What scientific literature describes 

the permanence of fingerprint 

characteristics? 

● How much, if at all, does aging 

affect latent fingerprint 

characteristics? 

● How much, if at all, do 

fingerprints change as individuals 

age? 

● How much are fingerprint 

characteristics altered by 

particular physical activities (e.g., 

masonry)?

Morphogenesis of friction ridge skin:

[Babler, W. J., Dermatoglyphics – Science in Transition, 1991]

This chapter provides a full overview of the studies in the relation to the embryologic 

development of friction ridge skin starting around 10 weeks postfertilization. The understanding 

of the prenatal morphogenesis of dermatoglyphic traits is fundamental to the understanding of 

the relationship between dermatoglyphic features and birth defects. A full account is given of 

the development of the hand, the volar pads, the epidermal ridges (their proliferation on the 

dermis surface leads to the formation of minutiae) and dermal papillae. The process of ridge 

formation is not an event occurring simultaneously across the whole surface, but initiates at 

several points on the surfaces and spreads out until these fields of ridges finally meet. The 

factors affecting ridge configuration are discussed, including growth stress, topography of the 

volar pads, the surface distribution of nerves and bone development.

[Wertheim, K. and Maceo, A., Journal of Forensic Identification, 2002]

The authors studied the anatomical structure and development process of human friction ridge 

skin with the aim of explaining why friction ridge skin is unique and permanent. The authors 

discuss how the complexity of the histological arrangements through the biological 

development of the volar skin enforces individuality and how the cellular junctions ensure 

permanence. Extensive bibliographic material is provided.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 11 of 64

November 16, 2011

[Kücken, M. U., Forensic Science International, 2007]

The paper offers an extensive literature review in relation to the morphogenesis of friction ridge 

skin. Three potential processes are covered: the folding hypothesis, the nerve hypothesis and 

the fibroblast hypothesis. A mathematical model is then proposed suggesting that the general 

pattern arises as the result of a buckling (folding) process in a cell layer of the epidermis. 

Essentially in relation to level 1 features, the study confirmed that (1) primary ridges are formed 

as the result of a buckling process, (2) ridges form perpendicular to the lines of greatest stress, 

(3) volar pad geometry influences the fingerprint pattern and (4) the nervous system influences 

ridge formation.

[Wertheim, K., The Fingerprint Sourcebook, 2011]

Wertheim discusses in detail how the basis of uniqueness lies in embryology and how the late 

embryological and early fetal development periods are crucial in the pattern formation of friction 

ridge skin. The author shows using an extensive bibliography that even though genetic 

information directs cellular function and determines someone‟s appearance, so many steps 

and factors are involved between the genesis of the DNA-encoded protein and the final 

development of the body that even identical twins would develop distinguishable friction ridge 

skin patterns.

Permanence of friction ridge skin:
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 12 of 64

November 16, 2011

In addition to the biological foundations covered in the papers in relation to the morphogenesis 

of friction ridge skin, we draw attention to:

[Galton, F., 1892]

In addition to setting up a classification for fingerprint files, Galton, in 1892, confirmed the three 

basic tenets of the science of friction ridge skin examination: immutability (based largely on 

data provided by Herschel), uniqueness, and inalterability. His studies established that 

fingerprints were stable from their formation during fetal life until death and even after. They 

therefore grow as the body grows and are sharply defined until an advanced age when 

incipient ridges appear as the skin becomes thinner. He also attested that fingerprints were, in 

severe cases, obliterated by some injuries that could leave permanent scars (hard labour, use 

of peculiar tools, severe cuts, etc.) and therefore make the ridge at that part undecipherable. 

He concluded that though the general pattern of volar skin may be altered through time, the 

number of ridges, their embranchments and other minutiae remain unchanged.

[Stücker, M., et al., Journal of Forensic Sciences, 2001]

The authors studied the morphologic features of interpapillary ridges (also known as incipient 

ridges) at the skin surface with the aim of evaluating their frequency of occurrence and 

quantifying the difference between these lines and the papillary ridges. Hundreds of inked 

prints were examined and the authors concluded that these ridges are present in a large 

proportion of the population and that they develop or manifest throughout life. Also, a study on 

prints of twins and unrelated individuals seems to indicate a degree of heredity for these 

features.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 13 of 64

November 16, 2011

[Modi, S. K., et al., Automatic Identification Advanced Technologies, 2007 IEEE Workshop on, 

2007]

Skin quality changes over a lifetime and can influence fingerprint quality, and consequently, the 

quality of an image obtained by a fingerprint sensor. This article deals with the influence of 

quality on recognition performance as a function of age. The authors considered four age 

groups and showed that there was a statistical difference in image quality and minutiae count 

for fingerprints from these different groups (with the greatest impact on performance for the 

group over 62 years old). The author therefore concluded that quality is not the only factor that 

influences performance rates. Those other factors have to be considered in further researches.

[Maceo, A. V., The Fingerprint Sourcebook, 2011]

This chapter provides an extensive account of the anatomy and physiology of friction ridge skin 

building on an extensive biological literature. It describes the biological processes leading to 

the permanence of friction ridge skin. The effects of aging (flattened ridges and wrinkles) are 

explained. A full section also deals with the wound healing process and its effect on scar 

morphology.

Abnormalities and effects of activities on friction ridge skin:

[Haylock, S. E., Fingerprint Whorld, 1987]

Abnormalities in finger and palm prints can be congenital or acquired. The author, divided 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 14 of 64

November 16, 2011

these modifications into 3 groups: malformation of digits, disturbances in the epidermal ridges 

and traumas and diseases. These alterations may make the print‟s pattern unreadable, and 

the author explains how some traumas can momentarily alter the quality of a print (minor cuts, 

contact with rough surface, etc.), and how some other alterations can be permanent (deep 

cuts, severe burns, etc.). This article contains a list of possible alterations and their effects on 

fingerprints.

[Olsen, R. D., Scott's Fingerprint Mechanics, 1978]

Part of this book (p. 80-82) explains how professional occupations (such as glazier, plasterer, 

labourer and battery worker) or other physical activities can result in temporary or permanent 

damages to the ridge structure of skin. These injuries can lead to minor or total obscuration of 

ridges and can sometimes interfere with classification, which is to be remembered by experts. 

The author provides a list of several physical injuries (like creasing, scars) and examples of 

altered inked prints.

1.2. Minutiae Sample Sufficiency

1.2.1. What scientific literature describes 

the likelihood that observed 

minutiae originate from the same 

or different fingerprints? 

● What is known about the 

underlying distributions of 

Underlying distributions of minutiae in the general population: 

Importance is given here to studies engaged in a systematic acquisition of statistical data in 

relation to minutiae where the sample description and the acquisition mechanisms are fully 

disclosed. In his review chapter [Stoney, D. A., Advances in Fingerprint Technology, 2001]
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 15 of 64

November 16, 2011

minutiae in various populations?

● Does variation in minutiae 

frequencies (e.g., within a 

fingerprint class) influence the 

reliability of fingerprint 

comparisons?

● How does the number of 

minutiae required to achieve 

high likelihood vary with 

number of fingerprints being 

compared or the quality of the 

fingerprints?

● How does the likelihood differ 

when comparing two exemplars 

vs. a LP and an exemplar?

(see summary hereinafter), Stoney referred to other early attempts to acquire systematic data 

on fingerprint minutiae (work of Amy, Santamaria Beltran, Kingston, Gupta and Osterburg). 

However these studies all suffered from a lack of disclosure of the exact fingerprint samples 

studied or from a very limited sample size.

[Koristka, C., et al., Kriminalistik und forensische Wissenchaften, 1979]

Based on a sample of 102 ulnar loops and 102 whorls which were chosen from the right middle 

fingers and right thumbs of 204 individuals, the authors present the results of minutiae relative 

frequencies and surface densities on the finger. The 102 whorls came from 76 people, and the 

102 ulnar loops from 57 people. Minutiae were counted on a grid, which was overlaid on the 

inked impressions. In total, 9590 minutiae were counted. Twelve different types of minutiae 

were taken into account (including ending ridges, bifurcations and hooks, all of them 

considered iin two directions). 5425 of the minutiae came from whorls, corresponding to 53.2 

minutiae per fingerprint. On whorls, 2328 ridge endings, and 1603 bifurcations were counted; 

other types of minutiae were much less frequent. On ulnar loops, 4165 minutiae were counted, 

corresponding to 40.8 minutiae per fingerprint. From these minutiae, 2062 were ridge endings, 

and 1155 bifurcations. The authors then present maps of minutiae, where the relative 

frequencies of the different minutiae types are shown.

[Dankmeijer, J., et al., Acta Morphol. Neerl.-Scand., 1980]

The question of how many minutiae are necessary for identification when comparing 

fingerprints is explored in this paper. Samples obtained from 100 Dutch males have been 

analyzed with respect to finger, general pattern and hand. The statistical analyses showed that 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 16 of 64

November 16, 2011

both pattern and finger factors influence the number of minutiae. In particular, whorls have the 

highest minutiae counts followed by loops and last are arches; Thumbs have the highest 

minutiae counts then in decreasing order, ring fingers, middle fingers, little fingers and indexes. 

There is no correlation however between the right/left hand and the number of minutiae. The 

authors conclude that the number of minutiae needed for identification, therefore, may vary 

according to finger and general pattern as well as sex and population group of individuals.

[Loesch, D. Z. and Martin, N. G., Annals of Human Biology, 1984]

The authors present a multivariate analysis of several characteristics of ridge patterns in the 

middle and ring fingers of the right hand including relationships between minutiae and general 

characteristics. Descriptive statistics for fingerprints obtained from 38 females and 63 males of 

European origin are presented. Six different variables have been taken into account: (i) the 

ridge count, (ii) ridge density, (iii) the total number of ridge endings and bifurcations, (iv) 

ridge/furrow width ratio, (v) convexity of pattern and (vi) pattern intensity index. Ridge groove 

width and ridge breadth are the two factors reported to show the most differences between 

males and females. Correlations between the variables of one finger, as well as between 

adjacent fingers on a lower level, have been found; factor analysis further describes the 

relationships between these variables related to the general pattern and minutiae. Negative 

correlations between ridge ends and ridge breadth has been found, as well as between 

junctions and pattern intensity (and therefore ridge count).

[Champod, C., Institut de Police Scientifique et de Criminologie, 1996]

On a large sample of inked fingerprints from male subjects (321 right loops on right index 

fingers, 365 right loops on right middle fingers, 118 left loops on left middle fingers and 173 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 17 of 64

November 16, 2011

whorls on right index fingers), the author investigates different links between minutiae and 

other variables. General pattern, finger number, ridge count, minutiae type, minutiae position, 

minutiae direction, minutiae density and the distance between several points making up a 

combined minutia are all investigated. The results obtained were as follows:

– The number of minutiae depends on the location of the fingerprint area being studied 

(Delta and the center being the most dense)

– The presence/absence of a delta and center influences greatly the number of neighboring 

minutiae.

– The top parts of fingerprints show the least variation in terms of minutiae number

– Minutiae distribution in the studied areas mainly follows a Poisson distribution.

When comparing two fingerprints using the model presented in this thesis, results tend to 

support the proposition that individualizing a fingerprint requires more than a fixed number of 

minutiae that should be in agreement (without discrepancy) between two impressions. On the 

other hand this probabilistic estimate for a given configuration of minutiae depends on the 

anatomical position of the area under comparison.

[Gutièrrez, E., et al., Forensic Science International, 2007]

The authors analyzed the fingerprints of 200 index fingers (100 from males and 100 from 

females). They studied the general patterns (arches, loops and whorls) and counted the total 

number of minutiae as well as their type. The most common type of minutiae was ridge ending, 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 18 of 64

November 16, 2011

followed by opening and closing bifurcations; all the others appeared with a frequency lower 

than 5%. The distribution of the minutiae was not homogenous for the area of the fingerprint; 

the density of minutiae was greater in the center and delta than in the periphery. There is also 

a correlation between the general pattern and the total number of minutiae found; whorls 

showed the highest number, followed by loops and arches. Finally, males present a higher 

number of minutiae, especially in the periphery.

[Seweryn, P., Problemy Kryminalistyki, 2005]

Study of the statistical distribution of minutiae observed on 400 fingerprints (right and left index) 

from 200 individuals (178 males and 22 females) held on police files from Southern Poland. 

Minutiae were manually counted and classified according to their types (ridge ending, 

bifurcations and a set of combined minutiae). Relative frequencies are given, showing the large 

relative abundance of ridge endings (opening and ending) and bifurcations compared to the 

other types of minutiae considered. One main outcome is the observation that the density of 

minutiae in the index varies according to the general pattern of the fingerprint (arch, loop or 

whorl). A rounded mean number of minutiae of 86 minutiae was counted on whorls, 80 on 

loops and 72 on arches.

[Cabanyes Cordero, D. E., Ciencia policial, 2010, Gómez Marín, J., et al., Ciencia policial, 

2010]

The study sets three main goals: (1) Establishing the frequency of minutiae given general 

pattern, orientation and position on the fingerprint; (2) Studying if there are any differences in 

minutiae frequency between sexes, minutiae type, finger position or area under study; (3) 

Completing the “empirical method” used in fingerprint identification by calculating the 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 19 of 64

November 16, 2011

discriminating power, the error rate, thus providing a scientific basis required by the judiciary.

The population of interest grouped 5000 women‟s fingers and 5000 men‟s fingers from the 

Spanish detainees archives, divided equally among their pattern (125 per finger and 

pattern/1250 for each of the 4 pattern types for each sex). The entire fingerprint is divided into 

four square sectors by placing a cross on the center. The sectors are numbered in a clockwise 

fashion, with sector 1 being the top left. Eighteen types of minutiae types were taken into 

consideration; 4 different types of endings and bifurcations (to the left, right, top or bottom of 

the print) as well as different combined minutiae. No significant difference between male and 

female was reported. In all sectors, there was a majority of ridge endings, followed by 

bifurcations; combined minutiae were much rarer. This was true for all general patterns. To 

conclude the study, frequency calculations for combinations of minutiae are proposed and 

carried out based on the hypothesis of independence between features. In the appendix, 

frequencies of general patterns based on a large sample, for all fingers and for male and 

female subjects separately, are provided.

[Gutièrrez-Redomero, E., et al., Forensic Science International, 2011]

A sample of inked prints from 100 males and 100 females of the Spanish population (2000 

fingerprints) has been used in order to describe the distribution of minutiae on the fingers. 

145,794 minutiae were analyzed in this study. Analyses were carried out by dividing the finger 

in four sectors, as well as separating the inside from the outside of a circle with a radius of 15 

ridges. Twenty different types of minutiae are defined and counted in the 8 different areas 

defined by the circle and the sectors. Correspondence analysis has been used for the analysis 

of different relationships such as that between general pattern and finger number (which is 

significant), between minutiae and finger number (which is significant as well), as well as sex 

and minutiae by area and by finger. Differences in the frequency of minutiae were found not 

only between the sexes and the different fingers, but also between the different areas defined; 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 20 of 64

November 16, 2011

endings have a lower frequency in the central area of the fingerprint than in the periphery, 

while the contrary is true for bifurcations and convergences. More complex relationships are 

also explained.

Spatial densities of minutiae:

Distributions of minutiae on the surface have been explored by [Champod, C., Institut de Police 

Scientifique et de Criminologie, 1996] (see above summary). It is reported that core and delta 

are richer zones in terms of number of minutiae compared to the periphery of the pattern. 

Hence spatial distribution of minutiae positions depends on the general pattern (more generally 

on the ridge flow: level 1 features). Similar observations were made by [Chen, Y. and Jain, A., 

Advances in Biometrics: Third International Conference, ICB 2009, Alghero, 2009], [GutièrrezRedomero, E., et al., Forensic Science International, 2011] (see above summaries) and to a 

limited extent by [Ross, A., et al., Pattern Analysis and Machine Intelligence, IEEE 

Transactions on, 2007].

Minutiae distribution among relatives and twins:
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 21 of 64

November 16, 2011

[Okajima, M., American Journal of Human Genetics, 1967]

Individual differences in minutiae were investigated among one population and on the heel of 

the foot. One hundred seven (107) pairs of Japanese twins between 12 and 17 years old were 

included. The sole prints were investigated, since in this area, the minutiae frequency cannot 

be dictated by the turns of ridges. A circular area with a radius of 18 ridges was used for 

counting. Each end, fork, island or short break counted as 1, enclosures, long breaks and 

minutiae composed of three ridge terminals counted as 2. The mean count of minutiae thus 

obtained is higher for males than for females. The differences between means of right and left 

feet are small (1.0 for males and 2.6 for females). An analysis of the correlation coefficients 

between the number of minutiae of homologous feet of twins results in larger correlation in 

monozygotic than in dizygotic twins. This shows that there is a genetic component to the 

variation of the frequency of minutiae in the calcar area of the feet.

[Okajima, M. and Usukara, K., Human Heredity, 1984]

Data concerning the total minutiae count and the proportion of bifurcations from the palms of 

20 pairs of monozygotic and 20 pairs of dizygotic twins is presented. The correlation of the total 

minutiae count and of the proportion of bifurcations is larger for monozygotic than for dizygotic 

twins. The authors conclude that this shows a genetic determination both of total minutiae 

count and proportion of bifurcations. The study also demonstrated that females showed 

significantly fewer minutiae than males.

[Jain, A. K., et al., Pattern Recognition, 2002]

This paper relates to the distinctiveness of biometric characteristics in order to establish the 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 22 of 64

November 16, 2011

performance limits of biometrics-based verification systems. It focuses on fingerprints and 

briefly reviews the genetic influence and intrauterine forces which affect the general 

characteristics of the fingerprint pattern and minutiae. The study was performed by comparing, 

based on minutiae, fingerprints from a population of twins (94 couples) and fingerprints from 

unrelated people. The study confirmed that a large class correlation exists between identical 

twin fingerprints. Based on minutiae, twin-twin fingerprints are generally more similar than twinnon twin fingerprints but results of the same order are obtained when comparing fingerprints 

with different general pattern from unrelated people to fingerprints with same general pattern 

from unrelated people. It is concluded that twin fingerprints can be distinguished using an 

automatic fingerprint identification system even if the accuracy is slightly lower than for non 

twins.

[Srihari, S. N., et al., Journal of Forensic Identification, 2008]

This study of twins (298 twin-pairs, 42 of which are fraternal twins) shows that twins‟ 

fingerprints are more likely to show the same general pattern for a given finger (56.92% for 

identical twins, 39.44% for fraternal twins and 31.76% for non-twins). After minutiae extraction 

and matching, the false positive rate obtained for twins is 6.17%, and 2.91% for non-twins. 

Testing of the distributions of match scores shows that the distribution for twins is different than 

that for comparisons between impressions from the same finger. The distribution for fraternal 

twins does not differ from that of identical twins, and the statistical test used does not formally 

show a difference between the distribution for twins and non-twins; it is concluded however that 

the similarity of fingerprints of twins is different from the similarity between arbitrary fingers.

[Sarkar, N. C., 2004]

Based on different tests carried out on a sample of 2010 fingerprints from 201 males and 2020 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 23 of 64

November 16, 2011

fingerprints from 202 females, concerning both level I and level II features, and integrating 

familial analysis, the author concludes on the following trends on level 2 features (the work 

offers in depth data on other dermatoglyphics traits): 

– The distribution of total finger ridge counts and total finger minutiae count are nonGaussian and characterized by flat peaks. Deviation from normality is not statistically 

significant for both total ridge counts and total finger minutiae count.

– Ridge endings, out of eight minutiae types that were considered, show a preponderance 

over other types, and the least frequently occurring minutia is the connecting ridge. Two 

minutiae types, ridge endings and forks, together represent more than 80% of the total 

minutiae count while the remaining six types represent only about 20%.

– Maximum occurrence of minutiae has been noted in the thumb followed by the ring 

finger, while minimum occurrence has been noted either in index or little finger.

– For total ridge counts and total minutiae count, fingers could be classified into two 

groups: (a) thumb and ring finger, (b) index, middle and little finger. Both total ridge 

count and total minutiae count also bear high hereditary significance.

– Mean minutiae count in males is significantly higher than that in females.

– Values of correlation for familial combinations except parent-parent are positive and 

most of them are statistically significant. The values of correlation for bifurcation and 

ridge ending are similar to each other and are at par with correlation values for total 

minutiae count, but higher than those of other minutiae types.

– Two minutia types, bifurcation and ridge ending along with a total minutiae count bear 

strong hereditary significance. These two minutiae types, out of eight different minutia 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 24 of 64

November 16, 2011

types, show very high heritability. Because of this high hereditary significance, fork and 

ridge ending may be useful as marker characters in genetical analysis as well as in 

personal identification

– Mean values of total ridge counts and total minutiae count for whorls are significantly 

higher than those for loops.

– The values of the ratio between mean minutiae count and mean ridge count is maximal 

in thumbs and decreases gradually from radial to ulnar fingers and finally reduced to its 

minimum in little fingers, irrespective of pattern type, hand and sex.

[Liu, Y. and Srihari, S., Computational Forensics, 2009]

A quantitative analysis of the discriminability of both identical and fraternal twin fingerprints on 

a new data set (227 pairs of identical twins and fraternal twins) using a state of the art 

fingerprint verification system is presented. Comparisons are based on the ridge flow and the 

minutiae. The analysis of level 1 characteristics suggest that fingerprint class in twins is highly 

correlated and therefore observing the same type of ridge flow between twins is more probable 

than in non-twins. Furthermore, results show that the minutiae pattern is more similar between 

twins than between unrelated individuals. Nevertheless, the twin fingerprints are discriminable 

with a slightly higher error rate than for non-twins, and the error rate for identical twins is 

slightly higher than that for fraternal twins.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 25 of 64

November 16, 2011

Probabilities associated with minutiae configurations:

For research before 1995, we refer to the review chapter by Stoney [Stoney, D. A., Advances 

in Fingerprint Technology, 2001], the additional research that followed is added hereinafter.

[Stoney, D. A., Advances in Fingerprint Technology, 2001]

A review of models measuring the rarity of fingerprint features from 1892 to 1999 is proposed. 

Out of the fifteen models presented, six are grouped together in a single class since they 

approach the question in the same way; 10 different approaches are therefore presented. All 

approaches are explained concerning the characteristics used and their 

description/measurement, as well as the probabilistic approaches employed and the results 

obtained. All of these approaches concern minutiae described using type and position, or only 

one of these two elements. Furthermore, some of these models address only the rarity of a 

given configuration, while others include a consideration of the correspondence observed 

during a comparison, or rather, a consideration of differences that are allowed during the 

comparison. All of the models yield numbers that highlight the variability of fingerprints. After 

this description of the data and approach used, the models are critically discussed. Finally, the 

author‟s conclusion highlights the weakness of the scientific foundation of fingerprint 

individuality, based on the fact that there while a number of models had been proposed, these 

were in general established on the basis of little data (with one exception), and in 2001, none 

of the models had been tested.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 26 of 64

November 16, 2011

[Pankanti, S., et al., Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2002]

The authors quantify the amount of information available in minutiae features to establish a 

correspondence. An expression for the probability of a false correspondence is derived, taking 

into account minutiae-based representations. The results obtained using this expression are

then compared to typical fingerprint matcher accuracy results. Results show that automatic 

fingerprint matching is not infallible, and thus led to some false associations. The strength of 

the evidence was highly influenced by the noise in the input fingermark. The theoretical limit of 

an automatic fingerprint verification system, as represented by the theoretical expression for 

the probability of a false correspondence, has not been reached by the systems in use. It 

would be of interest to explore additional complementary representations of fingerprints for 

automatic matching, as the systems that are based solely on minutiae generally use only a part 

of the discriminatory information available in the fingerprints.

[Neumann, C., et al., Journal of Forensic Sciences, 2007]

A model, taking into account minutiae configurations which are described using their relative 

orientation and position, as well as the type of the minutiae, is proposed. A means of modeling 

within-finger variability is proposed, and computations of likelihood ratios (LRs) are shown. 

Large databases are used for the establishment of the model, and it is tested on simulated 

cases where the ground truth is known. These tests show in particular that large LRs can be 

obtained for small numbers of minutiae. Also, as the number of minutiae in a configuration 

increases, the LRs overall increase. However, large differences in the order of magnitude of 

LRs are obtained for a given number of minutiae, highlighting that a given number of minutiae 

is not a sufficient indicator of rarity when dealing with low volumes of minutiae (i.e. 3 to 12) in 

latent prints..
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 27 of 64

November 16, 2011

[Su, C. and Srihari, S., Computational Forensics, 2009]

The authors present a model of the distribution of fingerprint features (ridge flow and minutiae) 

and use it for estimating the individuality of fingerprints. To this end, three metrics are used: (i) 

probability of random correspondence (PRC) of 2 individuals, (ii) PRC between two individuals 

among a group of n individuals (nPRC) and (iii) PRC between a specific individual among 

others (specific nPRC). The model is tested using these metrics against data obtained from the 

NIST4 database. Results show that the modeled values follow those obtained empirically. 

Furthermore, these results also show that PRCs are reduced when more features are used.

[Dass, S. C., et al., Encyclopedia of Biometrics, 2009]

This paper gives an overview of the problem of fingerprint individuality, while focusing on 

challenges, models, and methods developed to study the extent of uniqueness of a fingerprint. 

Two previously published fingerprint individuality models are presented, and it is shown how 

fingerprint individuality estimates can be obtained. Then, these models are extended to a 

population of fingerprints, and experimental results, comparing probabilities of random 

correspondence based on database searches and based on the two models. The empirical 

results show that in some instances, one of these models provides estimates of probabilities of 

random correspondence that are close to the observed ones.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 28 of 64

November 16, 2011

[Egli, N. M., Faculty of Law and Criminal Sciences, 2009]

The model is established based on AFIS scores, thus taking into account minutia position and 

orientation, for groups of minutiae. A very large background database (over 600,000 

fingerprints, from over 60,000 ten-print cards) was used, for establishment and testing of the 

model. Within-finger variability is based on repeated impressions of a given finger, then the 

scores obtained are modeled (rather than modeling the characteristics directly); impressions 

from the finger of one donor are used for the establishment of the model, and impressions from 

a different finger are used for testing. Between-finger variability is extracted by confronting the 

crime-scene mark to the entire database. Testing using same source and different source 

comparisons (where the „different source‟ reference prints were chosen randomly) showed low 

rates of misleading evidence.

[Neumann, C., et al., Journal of the Royal Statistical Society, 2012]

Using the descriptors of fingerprint minutia configurations as in the previous paper (Neumann 

et al 2007), a new model is proposed. Not only is distortion now modeled completely, and used 

to generate data for the numerator of the likelihood ratio (LR) expressing the weight of the 

evidence, but it is also used to generate repeat impressions for assigning the denominator of 

the LR. Furthermore, for the first time, examiner influence is taken into account – i.e. the 

differences that will occur if different annotations of the same characteristics are carried out are 

explicitly modeled, and included in the numerator and denominator. Then, the model is 

submitted to a „hard test‟. Real cases have been selected, the marks and corresponding prints 

encoded, and then, the best match for the mark has been searched in the IAFIS database. 

These triplets (mark-print from presumably same source-closest non-match in large database) 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 29 of 64

November 16, 2011

were then used to test whether the measure computed indeed supported the hypothesis known 

to be true, or the alternative hypothesis. While the evidence obtained during this test is 

misleading in a percentage of cases that is not negligible, diagnostics of the measure that allow 

a large reduction in this percentage are proposed.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 30 of 64

November 16, 2011

1.3. Fingerprint quality

1.3.1. What scientific literature describes 

how LP quality affects the 

probability of correctly matching 

(e.g., individualization or 

identification) or excluding 

fingerprints?

● How is LP quality currently 

assessed? 

● What are the pertinent 

metrics?

● How do analysts accommodate 

print quality/ surface during 

comparison and how effective 

are the current approaches?

● What methods can enhance 

images without risking bias in 

results (e.g., due to altering 

image)? 

● What is the effect of aging and 

environment on print quality? 

● What is the effect of print 

development (and/or lifting) on 

print quality?

Quality metric:

[Hicklin, R. A., et al., Journal of Forensic Identification, 2011]

The authors of this paper conducted a survey to determine how fingerprint examiners evaluate 

the quality of latent and exemplar fingerprints. Eighty-six (86) latent print examiners were 

asked to perform the assessment of local and overall quality of a series of fingerprints. 

Examiners were asked to base their assessments on their fundamental understanding of 

friction ridge impressions with no operational goals or legal consequences. The results of this 

study are as follows: to an extent, consistency was observed between examiners in value 

determination, relationships between the overall perceived quality of a print and the size of 

clear ridge detail were highlighted, as well as relationships between quality, size and correct 

pattern classification. An analysis of the examiner‟s subjective assessments of fingerprint 

quality revealed useful information for the development of guidelines, metrics and software 

tools for assessing fingerprint quality.

[Li, Z., et al., Computational Intelligence and Software Engineering, 2009. CiSE 2009. 

International Conference on, 2009]

In this paper the authors present a novel method for the evaluation of the quality and the 

validity of the fingerprint image. This method is based on the extraction of 10 features from the 

fingerprint image including foreground area, global image quality, local orientation certainty and 

ridge and valley clarity measures. The Fuzzy Relational Classifier (FRC) then classifies these 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 31 of 64

November 16, 2011

● What are effects of 

positive/negative images or 

reverse latent prints (e.g., color 

reversal due to fuming with 

superglue)?

features. This classification includes unsupervised clustering and supervised classification 

approaches. Their results show that the method is effective for the assessment of fingerprint 

image quality.

[Alonso-Fernandez, F., et al., Biometrics: Theory, Applications, and Systems, 2007. BTAS 

2007. First IEEE International Conference on, 2007]

The authors of this paper compared several metrics for assessing the quality of fingerprint 

images using an optical and a capacitive sensor. Image quality is assessed by measuring one 

of the following fingerprints properties (features): (1) ridge strength or directionality, (2) ridge 

continuity, (3) ridge clarity, (4) integrity of the ridge-valley structure or (5) estimated verification 

performance. The following metrics were tested: (1) orientation certainty level, (2) ridge 

frequency, (3) local clarity score, (4) local orientation quality, (5) energy concentration in the 

power spectrum and (6) matcher performance. The main results of this study are as follows: (1) 

all quality algorithms are capable of rejecting images of bad quality for both sensors, (2) 

several fingerprint image quality measures are suitable for optical and capacitive devices but in 

general, the discrimination capability is lower for the optical sensor than for the capacitive one 

and (3) the most discriminative measures with one sensor are the least discriminative ones 

with the other sensor, in particular with measures relying on grey level features being the most 

discriminative with the optical sensor and the worst with the capacitive one.

[Alonso-Fernandez, F., et al., Information Forensics and Security, IEEE Transactions on, 2007]

Existing approaches for fingerprint image quality estimation are first state, and then a number 

of fingerprint image quality estimation algorithms are tested. The authors divided the existing 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 32 of 64

November 16, 2011

approaches for fingerprint image quality estimation into 3 different classes: (1) Use of images‟ 

local features (Local Direction, Gabor Filters, Pixel intensity, Power Spectrum), (2) Use of 

images‟ global features (Direction Field, Power Spectrum) and (3) Use of classifiers (prediction 

of the matcher performance). The authors mention the ISO/INCITS-M1, which established a 

biometric sample-quality draft standard in which a biometric sample quality is considered from 

three different points of view. (1) the character (quality attributable to inherent physical features 

of the subject), (2) the fidelity (degree of similarity between a biometric sample and its source) 

and (3) the utility (impact of the individual biometric sample on the overall performance of a 

biometric system). In a second part, the authors studied the effect of rejecting low-quality 

fingerprint images using quality estimation algorithms. As a result they found a large 

improvement in the false rejection rate.

[Changlong, J., et al., Electronic Commerce and Security, 2009. ISECS '09. Second 

International Symposium on, 2009]

The influence of fingerprint sample quality on minutiae-based fingerprint recognition systems is 

examined. In a first step the authors evaluated the factors that influence the performance of the 

matching system and defined the absolute (Quality of Ridge-Valley Texture) and the relative 

(Common Area and Deformation) fingerprint sample quality. Then five different quality 

measures were selected and applied. The results show that these quality measures are 

correlated but sensor independent. It was also highlighted that the rejection of the samples with 

the lowest quality has a positive influence on the matching performance by decreasing the

error rates of recognition systems.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 33 of 64

November 16, 2011

Impact of quality:

[Blomeke, C. R., et al., 42nd Annual IEEE International Carnahan Conference on Security 

Technology, 2008]

The relationship between skin characteristics and fingerprint image quality is investigated. The 

studied skin characteristics are: moisture content, oiliness, elasticity and temperature. The 

authors collected fingerprint images from individuals over the age of 18. Measurements were 

recorded with nine commercially available fingerprint sensors, four capacitance sensors, four 

optical sensors, and one thermal sensor. The main results are as follows: (1) No correlation 

between the different characteristics was observed and (2) No significant correlation was 

observed between the different characteristics (variables) and the obtained quality scores.

[Dass, S. C., Information Forensics and Security, IEEE Transactions on, 2010]

The author studied the effect of noise in minutiae detection and localization due to poor image 

quality and its effects in fingerprint individualization. The problem is approached in two main 

steps: (i) the creation of a flexible class of statistical models for noisy minutiae, in order to 

derive the random correspondence probability (PRC). (ii) Those PRCs were then modeled as a 

function of the quality of the fingerprint pair via a log‐ linear random effects model. Empirical 

results showed the PRC increases as image quality becomes poorer. The methodology for the 

estimation of unknown parameters was developed in a Bayesian framework. Empirical results 

on two databases, one in-house and another publicly available, demonstrate how number of 

instances of misleading evidence increases as image quality becomes poor. The measure 

corresponding to the “12-point match” with 26 observed minutiae in the query and template 

fingerprints increases by several orders of magnitude when the fingerprint quality degrades 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 34 of 64

November 16, 2011

from “best” to “poor.” This study cautions the use of poor quality fingerprint images for the 

purpose of identification.

Image processing:

[Reis, G., 2007]

George Reis presents in the first chapter of his book the principles and fundamentals of image 

processing. These principles ensure that images are processed according to the rules of 

evidence and avoid the risk of bias in image processing. In chapter five of the book the author 

presents a list of valid image enhancement methods, which do not risk bias in the results. 

Finally, in the sixth chapter, it is described how the metadata of the image can be used and 

how to keep track of all the image enhancement methods which were applied.

Effects of aging and environment

[Modi, S. K., et al., Automatic Identification Advanced Technologies, 2007 IEEE Workshop on, 

2007]

The authors state that aging of skin results in loss of collagen and that aged skin is looser and 

dryer than younger skin. A decrease in skin firmness and some medical conditions such as 

arthritis may thus affect fingerprint quality during the capturing process necessary for 

automated system recognition. This research examines the effects of fingerprints from different 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 35 of 64

November 16, 2011

age groups (18-25, 26-39, 40-62, 62 and above) on quality levels, minutiae count, and 

performance of a minutiae-based matcher. The results showed a significant difference in 

fingerprint image quality across age groups, the elderly group (62 and above) had the worst 

quality; the overall quality score decreased with increasing variance as the age increased. 

Average minutiae counts, however, were within a similar range for all age groups, with only the 

variance increasing with age.

[Popa, G., et al., Romanian Journal of Legal Medicine, 2010]

The authors studied the evolution of the fingerprint aging process both indoors and outdoors, 

focusing on the pores, ridge thickness, valley width, number of minutiae and number of 

epithelial cells. They observed the disappearance of pores, minutia and epithelial cells as an 

effect of aging, caused by the dehydration of papillary lines resulting in shrinking of the ridges 

and an increase in valley width. These processes were faster on fingerprints left outdoors, 

because of environmental factors (not precisely identified in this paper). Fingerprint quality was 

of course affected by these degrading factors, presenting less detailed ridge contours and 

decreased number of minutia.

Effects of development techniques:

[Lee, H. C. and Gaensslen, R. E., Advances in Fingerprint Technology, 2001]

The authors discuss in chapter four of the “Advances in Fingerprint Technology (2nd Ed.)” 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 36 of 64

November 16, 2011

book various physical, chemical and illumination methods that are used for the detection of 

latent fingerprints. They explain which fingerprint detection method can be used on which type 

of surface to obtain the best results. The quality of the obtained prints is thus not directly 

dependent on the print development methods because those methods are chosen to obtain the 

best possible results. The quality of the detected prints is thus rather dependent on the latent 

fingerprint itself, on the type of surface and on the altering of the latent fingerprint due to 

environmental factors.

[Gupta, A., et al., Forensic Science International, 2008]

The authors of this paper conducted a study concerning the reproducibility of friction ridge pore 

detail in latent fingerprints. The two fingerprint development methods used in this study are 

cyanoacrylate fuming and ninhydrin. The authors used several fingerprints from the same 

donor and compared the quality of the pores of the detected fingerprints, aiming at learning 

more about the reproducibility of friction ridge pore detail. The authors concluded that the 

fingerprints detected by the two methods present big variations and friction ridge pore detail is 

not reproducible; friction ridge pore quality is thus mainly dependent on the quality of the 

fingerprint itself, before any enhancement techniques have been applied.

[Anthonioz, A., et al., Journal of Forensic Identification, 2011]

In this paper, the authors studied the reproducibility of the following third-level characteristics: 

pores, ridge edges and particular shapes of minutiae. The reproducibility of these features is 

examined on several recordings from the same finger, first acquired using only optical 

visualization techniques and second on impressions developed using the following common 

fingermark development techniques: DFO, ninhydrin, cyanoacrylate and powdering. The prints 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 37 of 64

November 16, 2011

were deposited on different porous and nonporous surfaces and the digital images were 

recorded at two different resolutions: 1000 and 2000 ppi. The main results are as follows: (1) 

the most reproducible features observed were minutiae shapes and pore positions along the 

ridges, (2) the third-level characteristics show very good reproducibility in high-quality images, 

directly obtained by coaxial episcopy, (2) the reproducibility of third-level characteristics is very 

difficult to obtain on marks detected with various detection techniques, particularly on porous 

surfaces, (3) the lack of reproducibility particularly penalizes small formations, precise shape of 

ridge edges, shape and size of pores, making it difficult to differentiate between real features 

and artifacts and (4) the increase in resolution did not result in better feature detection or 

comparison between images.

1.4. Fingerprint Matching

1.4.1. What scientific literature 

describes and justifies the role 

of automatic software 

algorithms in the fingerprint 

matching process?

● Ability of algorithms to operate 

as a stand-alone tool? 

● Application of algorithms to aid 

a human analyst?

● What is required to integrate 

algorithms more fully into the 

comparison process?

● What is the confidence in match 

results (e.g., Trade-off between 

[Bolle, R. M., et al., 2004]

This book presents the main aspects related to biometric systems and recognition. Two 

chapters are dedicated to system errors. The two principal types of errors performed in 

biometric systems (called false acceptation and false rejection) are presented and discussed in 

the context both of verification and identification purposes. Since these two types of errors are 

highly correlated, the choice of the operating point is crucial and application related. This 

specificity is discussed in this book and various ways of presenting error probabilities are 

presented.

[Dvornychenko, V. N. and Garris, M. D., 2006]

The purpose of the test summarized is to assess the state of the art in latent matchers and to 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 38 of 64

November 16, 2011

Type I and Type II error 

probability)?

● How does the accuracy of a 

human analyst compare to that 

of automated algorithms?

evaluate the ability of current latent matchers to field "semi-lights-out" latent search systems. 

All the steps involved in latent matching are described and the concepts of lights-out and semilights-out systems are introduced. Due to the important size of current latent databases, there 

is a need to produce latent search systems which are faster, and more accurate. Since 

generally it is not possible to process in a full lights-out manner, that is, completely without 

human intervention, semi-lights-out systems require human intervention exclusively for final 

verification and are less time-consuming than current latent matchers.

[Moses, K., The Fingerprint Sourcebook, 2011]

The benefits of the use of automated fingerprint identification systems (AFIS) as an essential 

tool for law enforcement agencies are presented. A complete description of the system‟s 

working principles is given, including AFIS functions and capabilities, system accuracy, and 

system and image requirements. The algorithm requirements for a successful data acquisition, 

data enrollment, feature extraction and matching process are also presented. The difference in 

performance between experts and automated systems is also discussed in this chapter. The 

authors highlight that "automatic fingerprint-matching algorithms are significantly less accurate 

than a well-trained forensic expert", but even so they can significantly reduce the work for 

forensic experts.

[Paulino, A. A., et al., Graphics, Patterns and Images (SIBGRAPI), 2010 23rd SIBGRAPI 

Conference on, 2010]

As latent print matching techniques still suffer from limitations in terms of accuracy and speed, 

and require heavy human intervention, the authors propose a method to improve latent to full 

fingerprint matching accuracy by combining manually marked minutiae with automatically 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 39 of 64

November 16, 2011

extracted minutiae. "[...] This framework consists of the following steps: (i) reconstruct the 

orientation field based on manually marked minutiae and singular points, (ii) enhance the latent 

using median ridge frequency computed in small image blocks and the reconstructed 

orientation field, (iii) match enhanced latents and rolled fingerprints, and (iv) combining the 

scores from two matchers using boosted max". It has to be noted that the improvement of the 

latent matching performance is quality independent.

The results presented show a better CMC curve (CMC for cumulative match curve) for the 

highest rank fusion than for manually marked minutiae.

[Indovina, M., et al., 2011]

The purpose of this test provided by the National Institute of Standards and Technology (NIST) 

Evaluation of Latent Fingerprint Technologies ‐ Extended Feature Sets (ELFT‐ EFS) is to 

evaluate the current state of the art on latent feature-based matching, by comparing the 

accuracy of searches using automatic feature extraction and matching alone with searches 

using different sets of features marked by experienced latent print examiner. The highest 

accuracy for all participant technology providers was observed for searches that included 

examiner-marked features in addition to latent image, while image-only search were more 

accurate than feature-only searches for most matchers. The score-based results provide an 

indication of how accuracy would be affected by an increase in database size. For most 

matchers, the addition of new EFS features provides an improvement in accuracy.

1.4.2. What scientific literature ACE-V:
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 40 of 64

November 16, 2011

describes and justifies 

standards regarding formulation 

and reporting of “Inclusion/ 

Identification; Exclusion; and 

Inconclusive” opinions?

1.4.3. What scientific literature 

describes, justifies and 

evaluates available 

mathematical models to assist 

in evaluating current or 

potential fingerprint matching 

methods?

1.4.4. What scientific literature 

characterizes the probability 

that two complete or sampled 

prints share a common source?

● What is the basis for the 

probability assessment?

● How much 

precision/uncertainty is 

associated with probability 

estimates?

● How much does the 

probability vary with amount of 

available information?

● How much similarity 

(particularly with respect to 

sampled minutiae) is needed 

to obtain a high probability of 

[Scientific Working Group on Friction Ridge Analysis Study and Technology (SWGFAST), 

2011]

This document details the steps of the ACE-V methodology (Analysis, Comparison, Evaluation 

and Verification) used for friction ridge examinations. These steps include both qualitative and 

quantitative aspects. Special attention is given to the evaluation, in which the examiner 

ultimately decides whether the unknown impression is from a different source or the same 

source as the compared impression. The possible conclusions reached after the decisionmaking process are exclusion, individualization and inconclusive. The significance of each of 

the three conclusions is explained in detail. A flowchart of the entire ACE-V protocol is 

represented in appendix.

[Langenburg, G., The Fingerprint Sourcebook, 2011]

Based on Popper‟s criteria, the author of this book chapter presents friction ridge principles (i.e. 

uniqueness and permanence) as appropriate scientific theories and laws, and friction ridge 

examination is presented as hypothesis testing. He also provides a state of the art (through 

2007) regarding scientific work carried out in order to answer questions related to uniqueness 

and permanence of friction ridge skin. Moreover, a review of available models to assess 

matching probabilities of a specific configuration of minutiae is provided. Finally, he shows the 

results of studies performed to test the ACE-V method used by fingerprint examiners to 

compare fingerprint impressions, such as the benefit of training or the absence of bias during 

the analysis step.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 41 of 64

November 16, 2011

match or confidence in mismatch? 

● How are the three levels of 

detail accommodated in the 

analysis? 

Numerical standard for conclusions:

The statistical studies exposed in section 1.2.1 bring support to the view that the strength of the 

association based on a configuration of minutiae will not solely depends on their number (as a 

fixed minimum standard may suggest) but also depends on their position, type and orientation. 

Additional references below address the same issue.

[Champod, C., Encyclopedia of Forensic Sciences, 2000]

This paper presents the two existing standards of proof, one using a predetermined minimum 

number of minutiae and one with no numerical standard. The author recommends the use of 

the latter, because identification process is a global assessment which balances both 

quantitative and qualitative aspects, rather than being a concept reduced to counting fingerprint 

minutiae. This statement is supported by the 1995 Ne‟Urim declaration, stating that “[n]o 

scientific basis exist for requiring that a predetermined minimum number of friction ridge 

features must be present in two impressions in order to establish positive identification”. 

Moreover, arguments are given in favor of a probabilistic approach and the possibility of giving 

qualified opinion based on dactyloscopic evidence in the decision making process, rather than 

the use of positive identification. The presented way forward is the adoption of a scheme of 

total quality management dealing with the various aspects of identification and training, 

laboratory procedures and audits.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 42 of 64

November 16, 2011

[Interpol European Expert Group on Fingerprint Identification II - IEEGFI II, 2004]

The report recognizes and endorses the basic principles of fingerprint identification. It contains 

detailed guidelines for analysis, comparison, evaluation, validation and verification of fingerprint 

details, introduces common terminology, identifies certain areas of risk and advises upon the 

application of general scientific principles and methodology which can be readily translated to 

the field of fingerprint identification. This leads to an entirely transparent, rigorous, 

reproducible, and verifiable methodology and process. Intentionally, no numerical standard for 

conclusions is proposed. Instead, some criteria are proposed to help assess the strength 

associated with the findings.

[Polski, J., et al., 2011]

The main recommendation of the present report states that “[t]here currently exists no scientific 

basis for requiring a minimum amount of corresponding friction ridge detail information 

between two impressions to arrive at an opinion of single source attribution.” Another milestone 

in this report is the recommendation that allows examiner to offer oral or written reports of 

testimony of probable or likely conclusions concerning source attribution of two friction ridge 

impressions being from the same source. Note the presence of appendix G referencing a 

bibliography of available research material.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 43 of 64

November 16, 2011

Concerning the addition of level 3 features:

[Jain, A. K. and Feng, J., Pattern Analysis and Machine Intelligence, IEEE Transactions on, 

2011]

The authors implement an algorithm for automated latent fingerprint matching using minutiae 

as well as extended features, including singularity feature, ridge quality map, ridge flow map, 

ridge wavelength map, and skeleton. The system was tested by matching 258 latent 

fingerprints against a background database of 29,257 rolled fingerprints.

The benefit of this approach over a baseline minutiae matcher is an increase of performance 

from 34,9 to 74 percent of rank-1 identification rate. The experimental results indicate that 

singularity feature, ridge quality map, and ridge flow map are the most effective features in 

improving the matching accuracy. The accuracy mainly depends on the latent fingerprint 

quality, and taking into account secondary features (level 3 features) will not lead to obvious 

improvement in the matching accuracy.

[Jain, A. K., 2011]

In this study, the author develops algorithms for encoding and matching extended features, 

develops fusion algorithms to combine extended features with minutiae information to improve 

fingerprint matching accuracy, and shows the contribution of various extended features in 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 44 of 64

November 16, 2011

latent fingerprint matching. An improvement in latent fingerprint matching accuracy on 

automated fingerprint identification systems (AFIS) is reached when taking into account 

extended features, such as ridge flow map, ridge wavelength map, and ridge quality map. 

Although the accuracy improvement is the highest with level 1 extended features, low quality 

latent fingerprints benefit the most from the use of level 3 extended features. In light of theses 

results, the author concludes that: "All extended features at Level 1 and Level 2 should be 

incorporated into AFIS [...]".

1.4.3 and 1.4.4: See section 1.2 above regarding level 2 features. 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 45 of 64

November 16, 2011

1.5. Analyst Considerations

1.5.1. What scientific literature 

characterizes the effect of analyst 

qualifications/ experience on 

fingerprint matching accuracy?

● What processes are used and 

what support is there for each 

process?

● What are the current methods 

and associated benefits of 

qualifying analysts?

● What on-going certification or 

training procedures are or should 

be used and what justification is 

there for the recommended 

methods? 

● Does variability in analyst 

background/ experience 

materially affect accuracy (e.g., 

probability of correct match/ mismatch decisions)? 

● What is an appropriate 

proficiency test and what 

justification is available for the 

[Wertheim, K., et al., Journal of Forensic Identification, 2006]

Data were collected during a comparison training exercise open to participants of any skill 

level, including participants without training or experience. To analyze the data, two separate 

groups were created: one of participants with more than one year of experience and another 

one of participants with one year of experience or less. Numerous data were analyzed, leading 

to important conclusions, among which it clearly appeared that: "participants with one year 

experience or less made a significantly higher ratio of errors (specifically erroneous 

individualizations) when compared to participants with more than one year of experience". 

Moreover, they also noticed that when the level of confidence (for the group of experienced 

examiners) decreases, the number of erroneous individualizations increases. Finally, the 

number of errors classified as „clerical (transcription) errors‟ remains constant; they are 

considered as independent of latent print difficulty or examiner ability.

[Koehler, J. J., Hasting Law Journal, 2008]

The author addresses several questions about current proficiency tests: Are they really 

efficient? Do they measure what we expect? How can we improve them? Properly designed, 

proficiency tests may provide a reasonable estimation of the rate at which false discoveries, 

false positive errors, and false negative errors occur. One conclusion offered by the author is 

that for a proficiency test to provide reasonable estimates of error rates in real casework, 

neither the examiners nor their supervisors should know that they are working on a proficiency 

test. The reason is that examiners performance is likely to improve when they know they are 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 46 of 64

November 16, 2011

test? being tested. Contextual blindness is required to ensure that examiners base their conclusions 

on the forensic evidence alone. Proficiency test participants should be a representative sample 

of laboratories and examiners drawn from the population of those who provide fingerprint 

testimony in court.

[Busey, T. A. and Dror, I. E., The Fingerprint Sourcebook, 2011]

This chapter is a combination of several studies that were conducted on the forensic expertise. 

It brings up the importance of experience and perceptual learning which improve the 

performance of the examiner of a latent fingerprint. It also talks about the configural processing 

used by the experts to unitize the individual features in a noisy latent print, allowing them to 

improve the quality of information extracted from this print. In addition to that, it is 

recommended that training should be with clear images since it develops the processes of 

external noise filtering and the enhancement of weak stimuli, and afterwards generalize this 

knowledge to noisy images. Furthermore, the examiners who rely on information that is not 

easy to verbalize should refine their learning by training on stimulus sets for which the ground 

truth is known and can be immediately verified. In fact, they create psychological dimension of 

stimuli, integrate and differentiate them depending on the nature of the task. Therefore, the 

correct working procedures should minimize the psychological and cognitive interferences in 

making fingerprint matching decisions.

[Busey, T., et al., Journal of Forensic Identification, 2011]

The authors of this paper wanted to determine which details fingerprint examiners rely on when 

conducting an examination. Two groups were considered: one of expert latent print examiners 

and one of novice participants. The eye positions were recorded while comparing the latent 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 47 of 64

November 16, 2011

print with the inked print. When there was no time limit, the experts spent approximately 50% 

more time inspecting the images than the novices. When 20 seconds were given to compare 

the prints, the experts were more consistent than the novices. Moreover, experts had higher 

accuracy, spent more time inspecting the latent prints, and showed shorter saccades (rapid 

eye movements during which no visual information can be acquired) than novices.

[Ulery, B. T., et al., Proceedings of the National Academy of Sciences USA, 2011, 

www.pnas.org/cgi/doi/10.1073/pnas.1018707108]

The goal of this study was to determine the frequency of false positive and false negative 

errors, to see if consensus exists between examiners‟ ability to reach a conclusion, and what 

are the factors influencing these values. The results indicate as a main outcome that: “False 

individualizations were made at the rate of 0.1% and never by two examiners on the same 

comparison. Five of the six errors occurred on image pairs where a large majority of examiners 

made true negatives. These results indicate that blind verification should be highly effective at 

detecting this type of error. Five of the 169 examiners (3%) committed false positive errors. 

False exclusions were much more frequent (7.5% of mated comparisons)”. The paper offers a 

rich analysis of other variables as well.

[Dror, I. E., et al., Forensic Science International, 2011]

The authors studied the inter- and intra-expert consistency. This study brings up some 

individual differences between the latent fingerprint examiners, which may be attenuated by a 

proper training tool that enables the examiners to correctly calibrate their thresholds. This 

problem might also be decreased by a possible best practice that identifies a priori which 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 48 of 64

November 16, 2011

marks are likely to produce such decision variations, and by applying special procedures such 

as the use of consensus high confidence minutiae, quality mapping and conservative selection 

procedures. Therefore, it is suggested to tailor procedures and best practices to difficult marks, 

since it will allow for higher quality work without requiring more resources, because it wisely 

and appropriately allocates resources to where they are needed. It is also recommended to 

isolate and document the initial analysis of the latent mark prior to moving to the other stages 

of the ACE-V process, in order to minimize the bias effect of the presence of a target 

comparison print (for further development on bias, see 1.5.5).

1.5.2. What scientific literature describes 

and justifies current quality control 

measures?

● Under what circumstances are 

blind controls routinely 

processed? 

● What are appropriate quality 

controls on LP matching and 

what justification is there for the 

recommended controls? 

[Gray, L., The Fingerprint Sourcebook, 2011]

This book chapter is a review specifically dedicated to the quality-assurance topic, and 

proposes information about accreditation and certification organizations. Special reference is 

given to the SWGFAST standards.

[United States Department of Justice and Office of the Inspector General - Oversight and 

Review Division, 2006, United States Department of Justice and Office of the Inspector 

General - Oversight and Review Division, 2011]

Although these two reports are not published in peer-reviewed journals, they bring a full 

account of the investigation undertaken by the Office of the Inspector General following the 

misattribution of a latent mark to M. Brandon Mayfield. It is followed by an assessment of the 

quality control measures in place further implemented after this incident.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 49 of 64

November 16, 2011

1.5.3. What scientific literature 

establishes the value of replication 

by a different examiner?

● How consistent are results by 

different examiners? 

● How much is error reduced by 

verification? 

● How consistent are results of reexamination by same examiner? 

1.5.4. What scientific literature examines 

the range of innate human pattern 

matching capabilities? 

● General pattern recognition

● LP matching-specific pattern 

recognition

[Langenburg, G., Journal of Forensic Identification, 2009]

This article fully answers this question (as well as the #1.6.3), since it covers the whole ACE-V 

process, with an assessment of the precision, accuracy, reproducibility, and repeatability of the 

process. The conclusions were numerous as many aspects of the ACE-V process were 

considered and tested. Briefly, about the value of replication, it was shown that during the 

verification every false positive was caught however none of the false negatives were detected. 

This demonstrated a strong resistance to bias with respect to the identifications but a high 

degree of bias considering exclusion (during a non blind verification for these participants).

Six fingerprint analysts participated in a series of tests which are divided in three principle 

steps: first analyzing sets of fingerprints with an ACE process, then conducting the verification 

for a set of fingerprints analyzed by another fingerprint expert, and finally re-presenting a 

certain number of comparisons to see if they will maintain their initial conclusions. The results 

can be briefly summarized as follow: 100% accuracy for the trials where an opinion of 

identification was reported (ACE and ACE-V processes) and 67% (ACE-V)/86% (ACE) for 

those with an opinion of exclusion; the precision during the ACE-V trials showed higher 

precision than ACE trials during the verification stage; regarding reproducibility 72% provided a 

100% consensus; and the author compared both reproducibility and repeatability in these 

experiments. 

[Busey, T. A. and Parada, F. J., Psychonomic Bulletin & Review, 2010]

This paper is a review which highlights different points regarding latent fingerprint experts, such 

as the way they conduct their examinations, the features or sources of information they use, 

the required evidence, in addition to the best approach for training new examiners. One of the 

well-known approaches is the ACE-V process. Experience allows the expert to outperform the

novice especially when the expert is accustomed to specify which features are essential and of 

great importance. About training, the best procedure should involve only clear prints not 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 50 of 64

November 16, 2011

corrupted by visual noise since it improves the perceptual representation of the stimulus and 

helps exclude external noise. The performance and the capability of a correct matching 

appeared to be related to the level of experience of the examiner, since experts tend to follow a 

certain configural processing of upright fingerprints and identify the diagnostic features. Their 

visual perception of the features and their ability of filtering the external noise are improved by 

the training giving therefore; a better performance result than the novices.

1.5.5. What scientific literature 

establishes the key sources of bias 

and characterizes the effectiveness 

of measures to mitigate the bias?

● Under what circumstances are 

“Exclusions” and “Inconclusives” 

verified during ACE-V?

● What knowledge does an analyst 

have regarding other case 

evidence?

● How much does such evidence 

influence accuracy? 

● How much is accuracy affected 

by “blind” or “non-blind” status?

● Under what circumstances do 

examiners/ verifiers compare 

several candidate prints versus 

verifying a single suspect print in 

comparison to a single crime 

[Langenburg, G., et al., Journal of Forensic Sciences, 2009]

Context and confirmation biases – respectively the exposure to extraneous information and the 

expectation of the observer – constitute the potential biases that might influence fingerprint 

experts during the verification stage of the ACE-V process. The study of these potential biases 

was the aim of this article which shows that fingerprint examiners can be biased especially 

during complex comparison trials. Moreover, they are more susceptible to this effect when it 

prompted towards inconclusive or exclusion conclusions compared to ones of individualization 

where they are trained to be more conservative; the risk and the penalties of incorrect 

individualization are far more severe than the other false conclusions. Therefore, in order to 

mitigate the bias, it is wisely recommended that blind testing verification is conducted during 

the situations cited above in addition to some random case selection and not in all routine 

examinations, since it is a waste of time and needlessly consumes significant personnel 

resources.

[Thompson, W. C., Wiley Encyclopedia of Forensic Sciences, 2009]

The author focused on the “observer effects” that influence the forensic scientists and hence, 

affect their interpretations leading to erroneous results. Such effects take place through 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 51 of 64

November 16, 2011

scene print? communications between the different people working on a case (such as police, lawyers, 

experts, etc.), or after being aware of the previous result of an analyst, or even when relying in 

part on subjective judgment to evaluate potentially ambiguous data. Numerous procedures 

might be employed in order to decrease this bias such as separating several laboratory 

functions and assigning them to different people, or performing the analysis and evaluation of 

various samples in a sequence so that analysis and interpretation of early samples cannot be 

influenced by knowledge of the later one. Another approach consists of conducting a blind or 

even double-blind procedure, with a "case manager" who is the only one aware of the broader 

facts of the case.

[Dror, I. E. and Cole, S. A., Psychonomic Bulletin & Review, 2010]

Various research studies that assess the different factors influencing the perception and 

comparison of fingerprint patterns, along with the forensic decision-making are well elaborated 

in this article. It also highlights some famous erroneous judgments such as the Mayfield case, 

since it shows the pernicious combination of an AFIS search and cognitive bias such as the 

explanation and dismissal of the discrepancies, which led to the bias of the subsequent 

examination. Latent print examination, despite its reputation for accuracy and objectivity, is 

subject to bias. However, this phenomenon is not observed among all examiners or scenarios, 

especially if they are analyzing a complete and high clarity print, or if they are aware that they 

are part of an experimental study.

[Dror, I. E., et al., Forensic Science International, 2011]

In this paper, the studies performed on actual latent fingerprint examiners revealed the 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 52 of 64

November 16, 2011

potential effect of the presence of a target comparison fingerprint on the analysis of the latent 

print. This research also reported some inconsistencies between and within experts during the 

analysis of latent marks. Therefore, it is highly suggested to follow a linear application of the 

ACE approach by first examining the latent mark, prior to looking at any potential comparison 

print, especially if the latent mark is of low quality, distorted or contains limited information. 

Furthermore, proper training can decrease the variation of consistencies among the examiners 

by developing an appropriate calibration tool that enables them to adjust their threshold so as 

to meet the standards in the field.

1.5.6. What scientific literature proposes, 

describes and evaluates alternative 

methods?

 What are the benefits 

and deficiencies of each method?

[Olsen, R. D. and Lee, H. C., Advances in Fingerprint Technology, 2001]

In addition with the conventional method ("based on the ridge characteristics and their unit 

relationship to one another"), there are seven alternative methods which can be used by latent 

print examiners for the evaluation and individualization of latent fingerprints (Osborn Grid, 

Seymour Trace, Photographic Strip, Polygon, Overlay, Osterburg Grid, or Microscopic 

Triangulation). According to the authors of this book chapter, all of these methods except the 

conventional one are limited since they only rely on spatial positions of the ridge 

characteristics; they don‟t take into consideration the relationship between the characteristics 

and all the other ridges or even the influence of distortion in the print. In addition, they don‟t 

explain the logical decisions that are required throughout the entire identification processes.

1.6. “End-to-End” Process 

reliability

1.6.1. What scientific literature describes It is clear there is relationship between 1.5 and 1.6. We shall only cover additional material 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 53 of 64

November 16, 2011

and evaluates current and potential 

methodologies? 

● Under what circumstances are 

specific methods appropriate and 

effective?

● How effective are the methods 

described? 

● What future procedures (e.g., 

DNA confirmation) are under 

development (e.g., by SWGFAST 

or SWGDAM)? 

● Does the size of the database 

(i.e., number of comparisons) 

influence methods?

1.6.2. What scientific literature 

establishes the basis for 

appropriate false match vs. missed 

match probabilities? 

● How do the probabilities differ for 

automatic and manual methods?

1.6.3. What scientific literature 

establishes the overall accuracy of 

current fingerprint analysis 

methods?

● What is the error performance of 

here.

[Dror, I. E. and Mnookin, J. L., Law Probability and Risk, 2010]

The authors review the problems and challenges brought by forensic tools such as AFIS. 

Before the use of databases, experts would generally compare a latent print with a quite limited 

number of tenprints, most of the time from individuals already suspected. With a system such 

as AFIS, latent prints can now be compared to many millions of prints stored in huge 

databases. The chances of finding by pure coincidence a lookalike print is much higher than 

when comparing a latent print to just a few dozens, hundreds or even thousands of prints prior 

to the introduction of AFIS. When database size increases, the chances that some print in the 

database will bear a high degree of resemblance to the latent in question also goes up. Despite 

this evolution, fingerprints experts have not changed and adapted their criteria for determining 

what counts as an identification as a result of AFIS.

1.6.2 and 1.6.3: See section 1.5 above plus the following contribution in relation to 1.6.3:
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 54 of 64

November 16, 2011

individual steps in each method?

● How much does accuracy vary 

with LP quality? 

● How much does accuracy vary 

with the number of minutiae 

examined? 

● How well does measured accuracy 

compare with examiner 

perception?

● How much does the number of 

comparisons performed in single 

evaluation influence accuracy? 

● How does accuracy vary for 

automatic versus manual 

examination? 

● How is “ground truth” (i.e., true 

match/ non-match status) 

established to support evaluations 

of examiner accuracy?

[Neumann, C., et al., Forensic Science International, 2011]

The purpose of the study is to assess the operational impacts (increase of evidence produced 

and benefits compared to the current protocols) of implementing a statistical model in 

fingerprint casework. Following an implementation (in a shadowing process) over 6 months, 

the study showed that among a total of 3600 additional marks (initially classify by the 

examiners having no value) but considered by the research team, only a few (38) led to 

additional evidence. That shows how efficient is the initial triage process carried out holistically 

by the laboratory. This filtering process is very efficient at maximizing the contribution of 

fingerprint evidence given time and resource constraints.

Among the fingermarks (70) taken through a comparison process but ultimately not used as 

evidence (reported inconclusive or no value), 20 led to evidence of association with weights 

quantified using the statistical model. The weights associated with these cases are of similar 

order of magnitude as the weights associated with the identification decisions reported by the 

laboratory. The paper provides a full description of the likelihood ratios associated with the 

reported cases by the laboratory and their relationship with the number of minutiae considered 

in the model. Finally the researchers have not observed any indication that the examiners were 

influenced by the number of previously recovered marks or by the presence of control prints

when deciding to recover marks or to consider them of value.

1.7. Future Research

What new technologies and areas of Focus will be given here on research avenues in relation to the questions raised by the RDT&E 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 55 of 64

November 16, 2011

research should be pursued with 

regard to latent print examination and 

analysis? (Note- this question does not 

require a list of references, it is for 

informational purposes only.)

IWG in this document. Needless to say that other areas such as the management of fingerprint 

identification activities (including AFIS operations and error management), the detection (and 

dating) of friction ridge skin marks both at the crime scene and in the laboratory or the 

preparation of witness statements and testimonies are also of paramount importance in 

forensic science.

Within the above restricted scope, the following lines of research constitute the priorities for 

SWGFAST (note that the order does not translate any priorities):

● Develop research in relation to the analysis phase of ACE-V with a view to help 

examiners to assign a level of complexity to friction ridge skin marks using 

dedicated tools such as automatic quality measurements.

● Research on AFIS systems aimed at (a) measuring the likelihood of observing close 

non-matches based on marks showing various levels of quantity and quality, (b) 

increasing accuracy by accounting for the discriminating value of additional features 

such as minutiae types or other features including level 3, or (c) defining the 

boundaries of fully automatic operations (i.e. lights-out) either on prints or marks. 

Interoperability of systems is also a key research area.

● Develop ways to handle decisions in complex comparisons in a way that reduce 

examiner variability, for example by taking advantage of a consensus set of features

provided by a pool of experts.

● Expand the systematic acquisition of data in relation to friction ridge skin 

features on areas such as palms, phalanges or upper fingertips. The acquisition 

should cover the range of features used by examiners in the comparison process, 

hence not only minutiae (and their combinations) but also scars, wrinkles, creases, 

warts, and level 3 features.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 56 of 64

November 16, 2011

● Develop proper mechanisms to interpret and assign weights to discrepancies

observed during the comparison process. Research in this area should study the 

distortion of the friction ridge skin when applied with various forces and movements 

on substrates both qualitatively and quantitatively.

● Pursue the research in relation to statistical models on large datasets in order to 

bring to examiners operational tools that can be applied in casework (both during the 

analysis stage and the evaluation stage of ACE-V).

● Study the statistical contribution of level 3 features in the identification process.

● Provide integrated technology to support the full examination process by e.g. an 

adherence to the steps of ACE-V, restricting case information to domain relevant, 

offering peer review mechanisms, a full documentation tuned as a function of 

complexity, automatic assessment of the markings and Q/A alarms.

● Research in relation to decision thresholds of examiners at the various stages of 

ACE-V, typically when large-scale AFIS systems are used.

● Because probabilities play such an important role in the decision-making process, 

there is a requirement for a training program for examiners covering for example 

empirical data regarding fingerprint features, models for friction ridge skin variability, 

inference and decision making. Such a program should allow a transition from the 

above research avenues to daily casework.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 57 of 64

November 16, 2011

References

Alonso-Fernandez, F., Fierrez, J., Ortega-Garcia, J., GonzalezRodriguez, J., Fronthaler, H., Kollreider, K., and Bigun, J., "A 

Comparative Study of Fingerprint Image-Quality Estimation 

Methods", Information Forensics and Security, IEEE 

Transactions on, vol. 2 (4), pp. 734-743, 2007.

Alonso-Fernandez, F., Roli, F., Marcialis, G. L., Fierrez, J., and 

Ortega-Garcia, J., "Comparison of Fingerprint Quality 

Measures Using an Optical and a Capacitive Sensor", in 

Biometrics: Theory, Applications, and Systems, 2007. BTAS 

2007. First IEEE International Conference on, 2007, pp. 1-6.

Anthonioz, A., Egli, N., Champod, C., Neumann, C., Puch-Solis, R., 

and Bromage-Griffiths, A., "Investigation of the 

Reproductibility of Third-Level Characteristics", Journal of 

Forensic Identification, vol. 61 (2), pp. 171-192, 2011.

Ashbaugh, D. R., "La Poroscopie", La gazette de la Gendarmerie 

Royale du Canada, vol. 45 (2), pp. 12-17, 1983.

Babler, W. J., "Embryologic Development of Epidermal Ridges and 

Their Configurations", in Dermatoglyphics – Science in 

Transition. vol. 27 (2), C. C. Plato, R. M. Garruto, B. A. 

Schaumann, and N. W. Paul, Eds. New York: Wiley-Liss, 

1991, pp. 95-112.

Blomeke, C. R., Modi, S. K., and Elliott, S. J., "Investigating the 

Relationship between Fingerprint Image Quality and Skin 

Characteristics", in 42nd Annual IEEE International 

Carnahan Conference on Security Technology, Prague, 

Czech Republic, 2008, pp. 158-161.

Bolle, R. M., Connell, J. H., Pankanti, S., Ratha, N. K., and Senior, A. 

W., Guide to Biometrics. New York: Springer-Verlag, 2004.

Busey, T., Yu, C., Wyatte, D., Vanderkolk, J., Parada, F., and 

Akavipat, R., "Consistency and Variability among Latent 

Print Examiners as Revealed by Eye Tracking 

Methodologies", Journal of Forensic Identification, vol. 61 

(1), pp. 60-90, 2011.

Busey, T. A. and Dror, I. E., "Chapter 15: Special Abilities and 

Vulnerabilities in Forensic Expertise", in The Fingerprint 

Sourcebook, International Association for Identification, Ed. 

Washington DC: National Institute of Justice, 2011, 

http://www.ncjrs.gov/pdffiles1/nij/225335.pdf.

Busey, T. A. and Parada, F. J., "The Nature of Expertise in 

Fingerprint Examiners", Psychonomic Bulletin & Review, vol. 

17 (2), pp. 155-160, 2010.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 58 of 64

November 16, 2011

Cabanyes Cordero, D. E., "Annexo: Cálculo De Las Frecuencias De 

Los Tipos Dactilares", Ciencia policial, vol. 101 pp. 61-69, 

2010.

Champod, C., "Reconnaissance automatique et analyse statistique 

des minuties sur les empreintes digitales", PhD in forensic 

science, Institut de Police Scientifique et de Criminologie, 

Université de Lausanne, Lausanne, Suisse, 1996.

Champod, C., "Fingerprints (Dactyloscopy): Standard of Proof", in 

Encyclopedia of Forensic Sciences, J. Siegel, P. Saukko, 

and G. Knupfer, Eds. London: Academic Press, 2000, pp. 

884-890.

Changlong, J., Hakil, K., Xuenan, C., Eunsoo, P., Junchul, K., 

Jinsoo, H., and Elliott, S., "Comparative Assessment of 

Fingerprint Sample Quality Measures Based on MinutiaeBased Matching Performance", in Electronic Commerce and 

Security, 2009. ISECS '09. Second International Symposium 

on, 2009, pp. 309-313.

Chen, Y. and Jain, A., "Beyond Minutiae: A Fingerprint Individuality 

Model with Pattern, Ridge and Pore Features", in Advances 

in Biometrics: Third International Conference, ICB 2009. 

LNCS 5558, M. Tistarelli and M. S. Nixon, Eds. BerlinHeidelberg: Springer Verlag, 2009, pp. 523-533.

Colletto, G. M. D. D., Kolya, M., and Zimberknopf, S., "Diagnosis of 

Twin Zygosity by Dermatoglyphic Index", Brasil. J. Genetics, 

vol. 10 (2), pp. 289-299, 1987.

Dankmeijer, J., Waltman, J. M., and De Wilde, A. G., "Biological 

Foundations for Forensic Identifications Based on 

Fingerprints", Acta Morphol. Neerl.-Scand., vol. 18 (1), pp. 

67-83, 1980.

Dass, S. C., "Assessing Fingerprint Individuality in Presence of Noisy 

Minutiae", Information Forensics and Security, IEEE 

Transactions on, vol. 5 (1), pp. 62-70, 2010.

Dass, S. C., Pankanti, S., Prabhakar, S., and Zhu, Y., "Individuality 

of Fingerprints", in Encyclopedia of Biometrics, S. Z. Li and 

A. Jain, Eds. New York: Springer Verlag, 2009, pp. 741-751.

Dror, I. E., Champod, C., Langenburg, G., Charlton, D., Hunt, H., and 

Rosenthal, R., "Cognitive Issues in Fingerprint Analysis: 

Inter- and Intra-Expert Consistency and the Effect of a 

`Target' Comparison", Forensic Science International, vol. 

208 (1-3), pp. 10-17, 2011.

Dror, I. E. and Cole, S. A., "The Vision in “Blind” Justice: Expert 

Perception, Judgment, and Visual Cognition in Forensic 

Pattern Recognition", Psychonomic Bulletin & Review, vol. 

17 (2), pp. 161-167, 2010.

Dror, I. E. and Mnookin, J. L., "The Use of Technology in Human 

Expert Domains: Challenges and Risks Arising from the Use 

of Automated Fingerprint Identification Systems in Forensic 

Science", Law Probability and Risk, vol. 9 (1), pp. 47-67, 

2010.

Dvornychenko, V. N. and Garris, M. D., "Summary of NIST Latent 

Fingerprint Testing Workshop", U.S. Department of 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 59 of 64

November 16, 2011

Commerce, National Institute of Standards and Technology, 

Washington DC 2006, 

http://fingerprint.nist.gov/latent/ir_7377.pdf.

Egli, N. M., "Interpretation of Partial Fingermarks Using an 

Automated Fingerprint Identification System", PhD in 

Forensic Science, Faculty of Law and Criminal Sciences, 

University of Lausanne, Lausanne, 2009.

Galton, F., Finger Prints. London: Macmillian and Co., 1892.

Gómez Marín, J., Ramón Ramón, M. Á., Gonzáles Arrieta, A., and 

García Sánchez, L. J., "Estudio De Las Frecuencias 

Fenotípicas De Los Puntos Característicos En 

Dactilogramas", Ciencia policial, vol. 101 pp. 5-60, 2010.

Gray, L., "Chapter 12: Quality Assurance", in The Fingerprint 

Sourcebook, International Association for Identification, Ed. 

Washington DC: National Institute of Justice, 2011, 

http://www.ncjrs.gov/pdffiles1/nij/225332.pdf.

Gupta, A., Buckley, K., and Sutton, R., "Latent Fingermark Pore Area 

Reproducibility", Forensic Science International, vol. 179 (2-

3), pp. 172-175, 2008.

Gutièrrez, E., Galera, V., Martínez, J. M., and Alonso, C., "Biological 

Variability of the Minutiae in the Fingerprints of a Sample of 

the Spanish Population", Forensic Science International, vol. 

172 (2-3), pp. 98-105, 2007.

Gutièrrez-Redomero, E., Alonso-RodrÌguez, C., Hernandez-Hurtado, 

L. E., and RodrÌguez-Villalba, J. L., "Distribution of the 

Minutiae in the Fingerprints of a Sample of the Spanish 

Population", Forensic Science International, vol. 208 (1-3), 

pp. 79-90, 2011.

Haylock, S. E., "Abnormalities in Dermatoglyphics", Fingerprint 

Whorld, vol. 12 (47), pp. 71-75, 1987.

Hicklin, R. A., Buscaglia, J., Roberts, M. A., Fellner, W., Burge, M. J., 

Monaco, M., Vera, D., Pantzer, L. R., C., Y. C., and 

Unnikumaran, T. N., "Latent Fingerprint Quality: A Survey of 

Examiners", Journal of Forensic Identification, vol. 61 (4), pp. 

385-418, 2011.

Hutchins, L. A., "Chapter 5: Systems of Friction Ridge Classification", 

in The Fingerprint Sourcebook, International Association for 

Identification, Ed. Washington DC: National Institute of 

Justice, 2011, http://www.ncjrs.gov/pdffiles1/nij/225325.pdf.

Indovina, M., Hicklin, R. A., and Kiebuzinski, G. I., "ELFT-EFS 

Evaluation of Latent Fingerprint Technologies: Extended 

Feature [Sets Evaluation #1]", U.S. Department of 

Commerce, National Institute of Standards and Technology, 

Washington DC, NISTIR 7775 2011, 

http://fingerprint.nist.gov/standard/cdeffs/Docs/ELFTEFS_PreliminaryReport_DRAFT_2010-01-26b.pdf.

Interpol European Expert Group on Fingerprint Identification II -

IEEGFI II, "Part 2: Detailing the Method Using Common 

Terminology and through the Definition and Application of 

Shared Principles", Interpol, Lyon 2004, 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 60 of 64

November 16, 2011

http://www.interpol.int/Public/Forensic/fingerprints/WorkingP

arties/IEEGFI2/default.asp.

Jain, A. K., "Automatic Fingerprint Matching Using Extended Feature 

Set", National Institute of Justice, 235577, August 2011, 

http://www.ncjrs.gov/pdffiles1/nij/grants/235577.pdf.

Jain, A. K. and Feng, J., "Latent Fingerprint Matching", Pattern 

Analysis and Machine Intelligence, IEEE Transactions on, 

vol. 33 (1), pp. 88-100, 2011.

Jain, A. K., Prabhakar, S., and Pankanti, S., "On the Similarity of 

Identical Twin Fingerprints", Pattern Recognition, vol. 35 

(11), pp. 2653-2663, 2002.

Koehler, J. J., "Fingerprint Error Rates and Proficiency Tests: What 

They Are and Why They Matter", Hasting Law Journal, vol. 

59 pp. 1077-1098, 2008.

Koristka, C., Nürnberger, N., and Georgi, G., "Zur 

Auftretenshäufigkeit Von Minuzien Nach Form Und Lage Im 

Fingerbeerenbereich", Kriminalistik und forensische 

Wissenchaften, vol. 35 pp. 21-30, 1979.

Kücken, M. U., "Models for Fingerprint Pattern Formation", Forensic 

Science International, vol. 171 (2-3), pp. 85-96, 2007.

Kumbnani, H. K., "Dermatoglyphics: A Review", in Anthropology 

Today: Trends, Scope and Applications. vol. The 

Anthropologist Special Volume No. 3, V. Bhasin and M. K. 

Bhasin, Eds. New Delhi: KRE publishers, 2007, pp. 285-295.

Langenburg, G., "A Method Performance Pilot Study: Testing the 

Accuracy, Precision, Repeatability, Reproducibility, and 

Biasability of the ACE-V Process", Journal of Forensic 

Identification, vol. 59 (2), pp. 219-257, 2009.

Langenburg, G., "Chapter 14: Scientific Research Supporting the 

Foundations of Friction Ridge Examinations", in The 

Fingerprint Sourcebook, International Association for 

Identification, Ed. Washington DC: National Institute of 

Justice, 2011, http://www.ncjrs.gov/pdffiles1/nij/225334.pdf.

Langenburg, G., Champod, C., and Wertheim, P., "Testing for 

Potential Contextual Bias Effects During the Verification 

Stage of the ACE-V Methodology When Conducting 

Fingerprint Comparisons", Journal of Forensic Sciences, vol. 

54 (3), pp. 571-582, 2009.

Lee, H. C. and Gaensslen, R. E., "Methods of Latent Fingerprint 

Development", in Advances in Fingerprint Technology, 

second ed, H. C. Lee and R. E. Gaensslen, Eds. Boca 

Raton: CRC Press, 2001, pp. 105-175.

Li, Z., Han, Z., and Fu, B., "A Novel Method for the Fingerprint Image 

Quality Evaluation", in Computational Intelligence and 

Software Engineering, 2009. CiSE 2009. International 

Conference on, 2009, pp. 1-4.

Liu, Y. and Srihari, S., "A Computational Discriminability Analysis on 

Twin Fingerprints", in Computational Forensics, 2009, pp. 

43-54, http://dx.doi.org/10.1007/978-3-642-03521-0_5.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 61 of 64

November 16, 2011

Loesch, D. Z., Quantitative Dermatoglyphics: Classification, Genetics 

and Pathology. Oxford: Oxford University Press, 1983.

Loesch, D. Z. and Martin, N. G., "Relationships between Minute 

Characteristics of Finger Ridges and Pattern Size and 

Shape", Annals of Human Biology, vol. 11 (2), pp. 125-132, 

1984.

MacArthur, J. W., "Reliability of Dermatoglyphics in Twin Diagnosis", 

Human Biology, vol. 10 (1), pp. 12-35, 1938.

Maceo, A. V., "Chapter 2: Anatomy and Physiology of Adult Friction 

Ridge Skin", in The Fingerprint Sourcebook, International 

Association for Identification, Ed. Washington DC: National 

Institute of Justice, 2011, 

http://www.ncjrs.gov/pdffiles1/nij/225322.pdf.

Mavalwala, J., Dermatoglyphics, an International Bibliography. 

Chicago: Mouton Publishers, 1977.

Modi, S. K., Elliott, S. J., Whetsone, J., and Hakil, K., "Impact of Age 

Groups on Fingerprint Recognition Performance", in 

Automatic Identification Advanced Technologies, 2007 IEEE 

Workshop on, 2007, pp. 19-23.

Moses, K., "Chapter 6: Automatic Fingerprint Identification Systems 

(AFIS)", in The Fingerprint Sourcebook, International 

Association for Identification, Ed. Washington DC: National 

Institute of Justice, 2011, 

http://www.ncjrs.gov/pdffiles1/nij/225326.pdf.

Neumann, C., Champod, C., Puch-Solis, R., Egli, N., Anthonioz, A., 

and Bromage-Griffiths, A., "Computation of Likelihood Ratios 

in Fingerprint Identification for Configurations of Any Number 

of Minutiae", Journal of Forensic Sciences, vol. 52 (1), pp. 

54-64, 2007.

Neumann, C., Evett, I. W., and Skerrett, J., "Quantifying the Weight 

of Evidence from a Forensic Fingerprint Comparison: A New 

Paradigm", Journal of the Royal Statistical Society, vol. 175 

(Part 2), pp. 1-26, 2012.

Neumann, C., Mateos-Garcia, I., Langenburg, G., Kostroski, J., 

Skerrett, J. E., and Koolen, M., "Operational Benefits and 

Challenges of the Use of Fingerprint Statistical Models: A 

Field Study", Forensic Science International, vol. 212 (1-3), 

pp. 32-46, 2011.

Okajima, M., "Frequency of Epidermal-Ridge Minutiae in the Calcar 

Area of Japanese Twins", American Journal of Human 

Genetics, vol. 19 (5), pp. 660-673, 1967.

Okajima, M. and Usukara, K., "Quantitative and Genetic Features of 

Epidermal Ridge Minutiae on the Palm of Twins", Human 

Heredity, vol. 34 pp. 285-290, 1984.

Olsen, R. D., "Occupational Damage and Bad Skin Condition", in 

Scott's Fingerprint Mechanics Springfield: Charles C. 

Thomas, 1978, pp. 80-82.

Olsen, R. D. and Lee, H. C., "Identification of Latent Prints", in 

Advances in Fingerprint Technology, second ed, H. C. Lee 
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 62 of 64

November 16, 2011

and R. E. Gaensslen, Eds. Boca Raton: CRC Press, 2001, 

pp. 41-61.

Pankanti, S., Prabhakar, S., and Jain, A. K., "On the Individuality of 

Fingerprints", Pattern Analysis and Machine Intelligence, 

IEEE Transactions on, vol. 24 (8), pp. 1010-1025, 2002.

Parsons, N. R., Smith, J. Q., Thönnes, E., Wang, L., and Wilson, R. 

G., "Rotationally Invariant Statistics for Examining the 

Evidence from the Pores in Fingerprints", Law Probability 

and Risk, vol. 7 (1), pp. 1-14, 2008.

Paulino, A. A., Jain, A. K., and Jianjiang, F., "Latent Fingerprint 

Matching: Fusion of Manually Marked and Derived Minutiae", 

in Graphics, Patterns and Images (SIBGRAPI), 2010 23rd 

SIBGRAPI Conference on, 2010, pp. 63-70.

Polski, J., Smith, R., Garrett, R., Ashbaugh, D. R., Babler, W. J., 

Chamberlain, P., Champod, C., Langenburg, G., Leben, D. 

A., Martin, K. F., Meagher, S. B., Moenssens, A. A., Norman, 

J., Taylor, M., Vanderkolk, J. R., and Zeelenberg, A., "The 

Report of the International Association for Identification, 

Standardization II Committee", National Institute of Justice, 

233980, March 2011, 

http://www.ncjrs.gov/pdffiles1/nij/grants/233980.pdf.

Popa, G., Potorac, R., and Preda, N., "Method for Fingerprints Age 

Determination", Romanian Journal of Legal Medicine, vol. 18 

(2), pp. 149-154, 2010.

Reed, T., Viken, R. J., and Rinehart, S., A., "High Heritability of 

Fingertip Arch Patterns in Twin-Pairs", American Journal of 

Medical Genetics Part A, vol. 140A (3), pp. 263-271, 2006.

Reis, G., Photoshop® CS3 for Forensics Professionals. Indianapolis, 

USA: Wiley Publishing, Inc., 2007.

Roddy, A. R. and Stosz, J. D., "Fingerprint Features - Statistical 

Analysis and System Performance Estimates", Proceedings 

of the IEEE, vol. 85 (9), pp. 1390-1420, 1997.

Ross, A., Shah, J., and Jain, A. K., "From Template to Image: 

Reconstructing Fingerprints from Minutiae Points", Pattern 

Analysis and Machine Intelligence, IEEE Transactions on, 

vol. 29 (4), pp. 544-560, 2007.

Sarkar, N. C., Finger Ridge Minutiae: Classification, Distribution and 

Genetics. Kolkata, India: Anthropologal Survey of India, 

2004.

Scientific Working Group on Friction Ridge Analysis Study and 

Technology (SWGFAST), "Standards for Examining Friction 

Ridge Impressions and Resulting Conclusions, Ver. 1.0", 

2011, http://www.swgfast.org/documents/examinationsconclusions/111026_Examinations-Conclusions_1.0.pdf.

Seweryn, P., "Frequency of Minutiae on Left and Right Hand Index 

Fingers", Problemy Kryminalistyki, (247), pp. 40-46, 2005.

Srihari, S. N., Srinivasan, H., and Fang, G., "Discriminability of 

Fingerprints of Twins", Journal of Forensic Identification, vol. 

58 (1), pp. 109-127, 2008.
SWGFAST Response to 

The Research, Development, Testing & Evaluation Inter-Agency Working Group

of the National Science and Technology Council, Committee on Science,

Subcommittee on Forensic Science

Page 63 of 64

November 16, 2011

Steinman, G., "Mechanisms of Twinning: I. Effect of Environmental 

Diverity on Genetic Expression on Monozygotic Multifetal 

Pregnancies", The Journal of Reproductive Medicine, vol. 46 

(5), pp. 467-472, 2001.

Stoney, D. A., "Measurement of Fingerprint Individuality", in 

Advances in Fingerprint Technology, second ed, H. C. Lee 

and R. E. Gaensslen, Eds. Boca Raton: CRC Press, 2001, 

pp. 327-387.

Stücker, M., Geil, M., Hyeck, S., Hoffman, K., Rochling, A., Memmel, 

U., and Altmezer, P., "Interpapillary Lines – the Variable Part 

of the Human Fingerprint", Journal of Forensic Sciences, vol. 

46 (4), pp. 857-861, 2001.

Su, C. and Srihari, S., "Probability of Random Correspondence for 

Fingerprints", in Computational Forensics: Third International 

Workshop, IWCF 2009. LNCS 5718, Z.J. M. H. Geradts, K. 

Y. Franke and C. J. Veenman, Eds. Berlin-Heidelberg: 

Springer Verlag, 2009, pp. 55-66.

Thompson, W. C., "Interpretation: Observer Effects", in Wiley 

Encyclopedia of Forensic Sciences, A. Moenssens and A. 

Jamieson, Eds. Chichester, UK: John Wiley & Sons, 2009, 

pp. 1575-1579.

Tietze, S. and Witthuhn, K., Papillarleisten-Struktur Der 

Menschlichen Handinnenfläche vol. 9. Neuwied: 

Luchterhand, 2001.

Ulery, B. T., Hicklin, R. A., Buscaglia, J., and Roberts, M. A., "A 

Study of the Accuracy and Reliability of Forensic Latent 

Fingerprint Decisions", Proceedings of the National 

Academy of Sciences USA, 2011, 

http://www.pnas.org/cgi/doi/10.1073/pnas.1018707108.

United States Department of Justice and Office of the Inspector 

General - Oversight and Review Division, A Review of the 

FBI's Handling of the Brandon Mayfield Case (Unclassified 

and Redacted). Washington DC, 2006.

United States Department of Justice and Office of the Inspector 

General - Oversight and Review Division, A Review of the 

FBI's Progress in Responding to the Recommendations in 

the Office of the Inspector General Report on the Fingerprint 

Misidentification in the Brandon Mayfield Case. Washington 

DC, 2011.

Wertheim, K., "Chapter 3: Embryology and Morphology of Friction 

Ridge Skin", in The Fingerprint Sourcebook, International 

Association for Identification, Ed. Washington DC: National 

Institute of Justice, 2011, 

http://www.ncjrs.gov/pdffiles1/nij/225323.pdf.

Wertheim, K., Langenburg, G., and Moenssens, A., "A Report of 

Latent Print Examiner Accuracy During Comparison Training 

Exercises", Journal of Forensic Identification, vol. 56 (1), pp. 

55-93, 2006.

Wertheim, K. and Maceo, A., "The Critical Stage of Friction Ridge 

and Pattern Formation", Journal of Forensic Identification, 

vol. 52 (1), pp. 35-85, 2002.