Detecting Fingerprint Alterations by Orientation Field and Minutiae Orientation Analysis John Ellingsgaard – [email protected] Ctirad Sousedik – [email protected] Christoph Busch– [email protected] Norwegian Biometrics Laboratory, Gjøvik University College, Norway 2 MOTIVATION Individuals try to deceive fingerprint identification It is possible to damage or alter the fingerprint by various means Many options – ranging from abrading, cutting and burning to sophisticated transplantations  Before mutilation After mutilation 3 MOTIVATION A fingerprint alteration detection method would: Enable more reliable identification of blacklisted individuals Reliable identification and re-identification of visa applicants  Before mutilation After mutilation 4 CHALLENGES Altered fingerprints are highly sensitive personal data Not possible to alter the fingerprint of a person in order to perform data collection Individuals with altered fingerprints will not cooperate Very difficult to collect a database of altered fingerprints! 5 DATABASE 116 altered fingerprints from: Brno: A collection of fingerprints containing a wide variety of dermatological diseases. GUC-100: An in-house database from GUC includes a few fingerprints containing dermatological diseases The Atlas of the Unusual Papilla Patterns: contains fingerprints from fingers altered by burns, acid burns, transplantation, miscellaneous injuries, and diseases. NIST SD14: contains some altered fingerprints along with 180 unaltered fingerprints 6 METHOD Preprocessing Segmentation by the standard deviation approach Morphological operations in order to include the altered areas FFT-based enhancement 7 METHOD Singular points density Alterations cause unnatural changes in the orientation field The changes can be seen as singularities Poincaré index  8 METHOD Singular points density The Poincaré index detects singularities in the altered areas But: It detects singularities also in low quality areas  9 METHOD Singular points density Quality estimation by using a Gabor filter approach by Olsen et al.   Combination of the Poincaré index responses with the quality estimation responses 10 METHOD Minutia orientation analysis Scarred areas generate additional minutia The orientations of the minutia do not follow the natural orientation field  11 METHOD Minutia orientation analysis Minutia extraction by using mindct  12 METHOD Minutia orientation analysis Largest orientation difference for each of the minutia found Map of differences of minutia orientations  13 METHOD Classification The same approach for the singular point density map and the minutia orientation map Division into 3 x 3 blocks Extraction of 21-bin histogram 189 feature vector dimensions 14 RESULTS Metrics: TADR = True Altered Detection Rate. Proportion of altered presentation characteristics correctly classified as being altered FNADR = False Non-Altered Detection Rate. proportion of altered presentation characteristics incorrectly classified as being non-altered 15 RESULTS  16 CONCLUSION AND FUTURE PLANS A fingerprint alteration detection method developed that outperforms the state-of-art method In the future: Testing on a larger scale database of altered fingerprints More complex features and feature fusions 17 Thank you John Ellingsgaard – [email protected] Ctirad Sousedik – [email protected] Christoph Busch– [email protected] References:  Jose Izquierdo (1997), altered his fingerprints by exchanging two portions of skin using a Z shaped cut.  Maltoni, A. et al. (2009), Handbook of Fingerprint Recognition, Springer Publishing Company, Incorporated.  S.S. Samischenko, Atlas of the Unusual Papilla Patterns/Atlas Neobychnykh Papilliarnykh Uzorov, Urisprudentsiia, Moscow, 2001.  M.A. Olsen, Haiyun Xu, and C. Busch, “Gabor filters as candidate quality measure for NFIQ 2.0,” in 5th IAPR International Conference on Biometrics (ICB), 2012, pp. 158–163.  Soweon Yoon, Jianjiang Feng, and Anil K. Jain, “Altered Fingerprints: Analysis and Detection,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 3, pp. 451–464, 2012.