Extraction of stable points from fingerprint images using zone Could-be-in theorem

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Abstract

This paper presents a novel zone Could-be-in theorem, and applies it to interpret and extract singular points (cores and deltas) and estimate directions of cores in a fingerprint image. Where singular points are regarded as stable points (attracting points and rejecting points just according to their clockwise or anticlockwise rotation), and pattern zones are stable zones. Experimental results validate the theorem. The corresponding algorithm is compared with popular Poincaré index algorithm under two new indices: reliability index (RI) and accuracy cost (AC) in FVC2004 datasets. The proposed algorithm are higher 36.49% in average RI, less 2.47 in average AC, and the advantage is more remarkable with the decrease of block size. © Springer-Verlag Berlin Heidelberg 2005.

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Wang, X., Li, J., Niu, Y., Chen, W., & Wang, W. (2006). Extraction of stable points from fingerprint images using zone Could-be-in theorem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3832 LNCS, pp. 251–257). https://doi.org/10.1007/11608288_34

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