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Journal of Electronic Imaging

Efficient fingerprint singular points detection algorithm using orientation-deviation features
Author(s): Foudil Belhadj; Samir Akrouf; Saad Harous; Samy Ait Aoudia
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Paper 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.

Paper Details

Date Published: 28 May 2015
PDF: 13 pages
J. Electron. Imag. 24(3) 033016 doi: 10.1117/1.JEI.24.3.033016
Published in: Journal of Electronic Imaging Volume 24, Issue 3
Show Author Affiliations
Foudil Belhadj, Ecole Nationale Supérieure d'informatique ex (Algeria)
Univ. de Bordj Bou Arréridj (Algeria)
Samir Akrouf, Univ. of Bordj Bou Arreridj (Algeria)
Saad Harous, United Arab Emirates Univ. (United Arab Emirates)
Samy Ait Aoudia, Ecole Nationale Supérieure d'informatique ex (Algeria)

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