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• W3204562017 abstract "Nowadays one of the most popular topics in fingerprint recognition academic research is the high-resolution fingerprint identification way. This technique has been prominently attractive to the worldwide scientific community thanks to the possibility of using level 3 features like pores which cannot be detected in lower resolution images. In this context, this chapter proposes two contributions: First, a pore detection method for high-resolution fingerprint image based on the morphological operation (skeletonization) and the labeled connect component method. Second, a new method to match pores without an alignment. Our matching approach is based on the contextual characteristics of the pore. It consists of positions and orientations of pore neighbors, which are defined as polar coordinates given in the polar system centered on the considered pore. The proposed algorithms are tested on a high-resolution fingerprint database. Experimental results show that our methods outperform the existing algorithms." @default.
• W3204562017 created "2021-10-11" @default.
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• W3204562017 date "2021-01-01" @default.
• W3204562017 modified "2023-09-24" @default.
• W3204562017 title "Fingerprint Recognition Based on Level Three Features" @default.
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• W3204562017 doi "https://doi.org/10.1007/978-3-030-81982-8_2" @default.
• W3204562017 hasPublicationYear "2021" @default.
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