Biometrics of Juveniles

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Marie-Françoise Vinet
il y a 6 ans
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1 Biometrics of Juveniles Sagem Sécurité

2 Juvenile Fingerprint Processing Juvenile fingerprints raise 2 main problems: size of the finger Juveniles 1

3 Juvenile Fingerprint Processing Juvenile fingerprints raise 2 main problems: Growth between 2 captures 2

4 Juvenile Fingerprint Processing * One important characteristic : Fingerprint frequency = average distance between ridges Depends of the age of the person, of the resolution (500 dpi,...) * in the usual fingerprint processing Acquisition Encoding Matching 3

sampling_frequency the continuous signal can be completely reconstructed from

5 Fingerprint Acquisition Signal & image sampling : Shannon theorem & Nyquist frequency If signal_frequency < Nyquist_frequency with Nyquist_frequency = ½. sampling_frequency the continuous signal can be completely reconstructed from the samples else there are aliasing effects: signal distortions (Fe=sampling_frequency) 4

6 Fingerprint Acquisition IQS (Image Quality Specifications) at 500 ppi resolution (500 pixels per inch) for the fingerprint acquisition with ten-print card scanner, live scanner, MTF 1,2 1 0,8 0,6 IQS specifications Scanner performance measure: MTF (Modulation Transfer Function), the spatial frequency response of the scanner, is a measure of the contrast reduction imposed by an imaging device 0,4 0,2 0 aliasing Period (pixels) Nyquist period MTF min IQS Example of a real! Aliasing is possible over Nyquist period measured (theoretical MTF min value for a sinusoid) with non uniform real signal Adult fingerprint period safe period safe period 5

Juvenile Fingerprint Characteristics higher frequency of the ridges 9 8 7 Period histogram Adults Juveniles (12 year old) 6 5 % 4 3 2 1 0 7,2 7,4 7,6

old) Adult period (pixels) 10 9,5 9 8,5 8 7,5 7 6,5 6 5,5 5 Juvenile fingerprint period real measures modelisation 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

7 Juvenile Fingerprint Characteristics higher frequency of the ridges Period histogram Adults Juveniles (12 year old) 6 5 % ,2 7,4 7,6 7,8 8 8,2 8,4 8,6 8,8 9 9,2 9,4 9,6 9, ,2 10,4 Period (pixels) Juvenile (12 y. old) Adult period (pixels) 10 9,5 9 8,5 8 7,5 7 6,5 6 5,5 5 Juvenile fingerprint period real measures modelisation «Ce document et les informations qu il contient sont la propriété de Sagem Sécurité. Ils ne doivent pas être copiés ni communiqués à un tiers sans l autorisation préalable et year écrite olde Sagem Sécurité.». 6

8 Juvenile Fingerprint Acquisition MTF At 500 ppi resolution: 1,2 1 0,8 0,6 0,4 0,2 At 200 ppi resolution: young people fingerprints are distorted by aliasing effects 200 ppi 1,2 1 0,8 0,6 0,4 0,2 0 aliasing Period (pixels) Nyquist period safe period adult fingerprint period 12y. old fingerprint period ~4y. old fingerprint period Period (pixels) Nyquist period safe period adult fingerprint period 12y. old fingerprint period ~4y. old fingerprint period 7

9 Juvenile Fingerprint Acquisition The juvenile fingerprint acquisition requires: high scan precision ppi resolution min to preserve fine and close ridges especially for very young people (< 6 years old) 8

10 Juvenile Fingerprint Processing Juvenile fingerprints raise many problems: small finger, growing with the age in the usual fingerprint processing Acquisition Encoding Matching 9

11 Fingerprint Encoding A fingerprint is a succession of ridges and valleys from which distinguishing features have to be extracted: Most widely used method: minutiae encoding ridge ending Bifurcation 10

12 Fingerprint Encoding Minutiae extraction: Filters allow for each pixel to compute the frequency and the direction of the lines Binary image restoration and minutiae localization 11

13 Fingerprint Encoding Another method: pattern encoding for each image bloc, direction θ frequency 1/λ phase δ computed by an adapted filter λ θ δ 12

14 Fingerprint Encoding Whatever the encoding method: minutiae encoding pattern encoding frequency features are needed and have to be calculated with filters in non usual intervals of search 13

15 Juvenile Fingerprint Processing Juvenile fingerprints raise many problems: small finger, growing with the age in the usual fingerprint processing Acquisition Encoding Matching 14

16 Juvenile Fingerprint Matching Matching a juvenile fingerprint versus an another one at the same age no problem versus an older one or an adult problem because Pattern matching uses frequency features Minutiae matching uses the geometric distribution of the minutiae 15

17 Juvenile Fingerprint Matching So, even if the matching allows: local distortions translations rotations it does not hit when the homothetie is too large mate = Matching_function (T, R, D, H ) (search) When there is a large difference in size between the search and the mate, accuracy can be significantly reduced 16

18 Juvenile Matching Solution Possible solutions: matching information which are static with the age (as ridge count): explicit or implicit use growing old model for juvenile fingerprints from the age of the person (if it is known) from calculating the ridge frequency Example of a juvenile fingerprint growing old (after or before coding) for minutiae matching 17

19 Juvenile Matching Solution the growing old solution allows to solve the juvenile matching problem No Hit Growing old Hit 18

20 Juvenile Fingerprint Matching The juvenile matching requires: a method taking into account the homothetie existing between juvenile and adult fingerprint, as well as translation, rotation and distortions A fingerprint growing process allows to solve this problem 19

21 Conclusion Fingerprint processing needs methods adapted to the problems raised by young people For each step, Acquisition Encoding Matching solutions exist! 20

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