Abstract
Fingerprint-based identification is the incredible mean of human authentication since ancient decades. Complex distortions involved during minutia-based matching of two impressions of the same finger make the matching very challenging in the literature. This paper presents a novel fingerprint-matching method based on the orientation analysis of fingerprints using local binary patterns (LBP) computed from fingerprint ridge orientation field. Alignment is performed using maximization of mutual information between orientation features extracted from the fingerprint images. The region of interest (ROI) is extracted by cropping the fingerprint image around the detected reference point. The matching performance using orientation local binary pattern (OLBP) descriptor has been evaluated on FVC2002, FVC2004 and FVC2006 databases using Chi-square test, Euclidean distance, and least square support vector machine (LSSVM). The experimental results show that the performance of LBP features computed from the orientation image is comparable to those achieved in the literature.









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Kumar, R. Orientation Local Binary Pattern Based Fingerprint Matching. SN COMPUT. SCI. 1, 67 (2020). https://doi.org/10.1007/s42979-020-0068-y
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DOI: https://doi.org/10.1007/s42979-020-0068-y