Abstract

This paper presents a novel algorithm for fingerprint matching using statistical descriptors. This fingerprint-matching algorithm overcomes the problems faced during matching of low quality fingerprint images. The steps of the algorithm include extraction of core point using Poincare index method, extraction of Region of Interest (ROI) around core point, and similarity evaluation of statistical descriptors using k-NN classifier. Statistical descriptors are computed from 16 Gray Level Co-occurrence Matrices (GLCM) from Extracted ROI. The proposed algorithm is evaluated on the FVC2002 DB2 database. The experimental results show the effectiveness of proposed algorithm. Computational efficiency is improved by considering the ROI of size 101 ? 101 around the core point.

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