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Efficient fingerprint singular points detection algorithm using orientation-deviation features

[+] Author Affiliations
Foudil Belhadj

Ecole nationale supérieure d’informatique ex. INI, Oued Smar, Alger 16270, Algeria

Univeristé de Bordj Bou Arréridj, El-Annasser, BP 64, BBA 34030, Algeria

Samir Akrouf

Univeristé de Bordj Bou Arréridj, El-Annasser, BP 64, BBA 34030, Algeria

Saad Harous

United Arab Emirates University, College of Information Technology, P.O. Box 17551, Al-Ain, United Arab Emirates

Samy Ait Aoudia

Ecole nationale supérieure d’informatique ex. INI, Oued Smar, Alger 16270, Algeria

J. Electron. Imaging. 24(3), 033016 (May 28, 2015). doi:10.1117/1.JEI.24.3.033016
History: Received January 22, 2015; Accepted April 30, 2015
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Abstract.  Accurate singular point (SP) detection is an important factor in fingerprint (FP) recognition systems. We propose an algorithm to detect SPs in FP images. Our idea is based on the observation that the orientation field (OF) at the regions containing SPs has high variation, whereas in the other regions, it is smooth. Thus, a pixel-wise descriptor that comprises orientation-deviation (OD)-based features is proposed to measure the OF variation in the local neighborhood of a pixel which we call OF energy. Candidate SPs are characterized by locations where the OF energy function has local gradual maxima. Furthermore, the OD-based descriptor exhibits some advanced topological properties, in particular the descriptor profile tendency, which are highly correlated with the SP type. These properties are used to filter out some spurious SPs. A second refining step based on an extended Poincaré index is then applied to keep only genuine SPs with their information. The proposed algorithm has the ability to accurately detect the classical singularities as well as the arch-type SP. Experiments conducted over the public databases FVC2002 db1 and db2 confirm its accuracy and reliability with a reduced false alarm rate in comparison to other proposed methods.

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Citation

Foudil Belhadj ; Samir Akrouf ; Saad Harous and Samy Ait Aoudia
"Efficient fingerprint singular points detection algorithm using orientation-deviation features", J. Electron. Imaging. 24(3), 033016 (May 28, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.3.033016


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