Slovak Fingerprint Individuality model

Zuzana Nemethova, Otokar Grosek, Martin Babinec and Marek Sys

Forensic Science Institute of Police Corps Forensic Science Institute of Police Corps &&

Department of Applied InformaticsDepartment of Applied Informatics and Information Technologyand Information Technology

8th INTERNATIONAL SYMPOSIUM ON FORENSIC SCIENCES, Sep 26th - 29th 2007, Šamorín-Čilistov, Slovak Republic

EN ISO/IEC 17025

In 2002 the ENFSI Board has approved the Policy Commitment on accreditation stating that until the end of the year 2008 all the members should have achieved or be taking steps towards the EN ISO/IEC 17025 compliant accreditation for their laboratory testing activities or other Quality Management standards with equivalent objectives

FSI and accreditation

a lot of questions were raised ...Could you find a probability of the individual

identification ? is it 99, 9% or 80%, how can you say it is 100%?

Could you find a probability of the false identification ?

Fingerprint Individuality model Galton (1892) – first model, 1/(64x109) Balthazard (1911) – 4 possible events Cummins and Midlo (1943) – pattern factor Roxburgh (1933) – polar coordinate system, correlation

among neighboring minutiae, fp quality, position of minutiae configuration relative to the pattern core

Osterburg (1977 – 1988) – relative frequencies of minutiae Champod and Margot (1995 – 1996) – 9 minutiae types,

1000 inked fp at 800 dpi, ridge = single pixel line, minutiae density, regional frequencies of minutiae types, relative orientation of minutiae

Meagher, Budowle, Ziesig (1999) – first experiment based on inter-comparing records of rolled fingerprints, simulated event - 4 minutiae - probability 1/1027

Our model of a fingerprint

we assume a fingerprint of each finger as a map of 54 x 54 cells in each cell there is possible only one

minutiae: ending ridge U bifurcation V dot B (omitted)

Our model of a fingerprint

we suppose 10 fingers for a person, and thus for each person we have a vector consisting from 10 54 54 = 291600 coordinates 0 stands for non-occurrence of a detail 1,2,3,4 possibilities are for U 5,6,7,8 for V 9 for B (omitted)

Thus for each cell we define a random variable, say X, which may take on 10 values. Clearly, these random variables do not have the same probability distribution.

Questions / hypothesizes

to specify probability distributions for each X test the independence for some specified cells/

regions of cells, using contingency tables; this may enables to determine some coefficients of association

to establish some inferences between cells estimation of the main factors (coordinates) using discriminant analysis we will try to find

a discrimination function in order to predict some incomplete fingerprints

Pilot 1

pilot 1 (2006) we have collected data of 100 fingers (just 10 persons) manually. too few data too time consuming

Pilot 1 data

4,12,U3 5,26 U2 5,11,U1 7,28,V2

7,9,V3 9,13,V1 11,31,U2 13,13,U1

14,14,V1 14,30,U4 15,22,V415,13,U3

16,11,U1 16,31,U2 17,20,V417,14,V1

17,11,U1 17,10,U3 18,22,U4 19,24,V4

19,13,V1 20,22,U3 21,10,U1 22,7,V1

22,8,U2 22,24,V422,27,U4 23,23,V4

23,15,U3 24,8,V1 24,24,U2 25,31,U2

25,27,U2 25,25,U2 25,24,U3 25,22,V1

25,14,V1 25,12,U1 26,13,U1 26,15,V1

26,18,V1 26,20,U1 27,27,V227,17,V1

28,8,U1 28,9,U1 28,14,B 28,7,V3

29,14,V1 32,10,V332,11,U3 32,12,U3

Pilot 2

pilot 2 (2007) – we have collected data of 1100 fingers using ISO tester software more data less time consuming FiMiViser – an application to visualize

statistical results

Pilot 2 - data

For 739 samples of all fingers (except the little fingers) we have

95% correlation in cells on the following lines:

Red: (16,2) (54,40)Green: (26,2) (54,31)Yellow: (49,2) (54,08)

angle: 45°

0

54

54

Our aim is

to find a relatively small number of cells << 54 54, which identifies uniquely a person, and calculate the number required for the coincidence

???

Zuzana NemethovaZuzana NemethovaForensic Science Institute of Police Corps Forensic Science Institute of Police Corps

nemethova@keupz.minv.skhttp://ifs.minv.sk/

Otokar Grosek, Martin BabinecOtokar Grosek, Martin Babinec, Marek Sys, Marek SysSlovak University of Technology Slovak University of Technology

Department of Applied Informatics andDepartment of Applied Informatics andInformation TechnologyInformation Technology[name].[surname]@stuba.sk

http://www.elf.stuba.sk/Katedry/KAIVT/