Palmprint matching using feature points and SVD factorisation

Omar Nibouche; Jianmin Jiang

doi:10.1016/j.dsp.2013.02.011

Palmprint matching using feature points and SVD factorisation

Omar Nibouche, Jianmin Jiang

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

In this paper, a new palmprint matching system based on the extraction of feature points is suggested. Using a scale-space representation, the points in question are corners formed by the intersection of creases and lines. Unlike minutiae, such points can still be extracted even on low resolution palmprints. Matching is carried out using an SVD factorisation of a proximity matrix and takes account of the coordinates of the detected points and their local texture. Our experiments have yielded some very good results evidenced by an EER of 0.10%.

Original language	English
Pages (from-to)	1154-1162
Journal	Digital Signal Processing
Volume	23
Issue number	4
DOIs	https://doi.org/10.1016/j.dsp.2013.02.011
Publication status	Published - Jul 2013

Access to Document

10.1016/j.dsp.2013.02.011

http://www.sciencedirect.com/science/article/pii/S105120041300033X

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abstract = "In this paper, a new palmprint matching system based on the extraction of feature points is suggested. Using a scale-space representation, the points in question are corners formed by the intersection of creases and lines. Unlike minutiae, such points can still be extracted even on low resolution palmprints. Matching is carried out using an SVD factorisation of a proximity matrix and takes account of the coordinates of the detected points and their local texture. Our experiments have yielded some very good results evidenced by an EER of 0.10%.",

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AB - In this paper, a new palmprint matching system based on the extraction of feature points is suggested. Using a scale-space representation, the points in question are corners formed by the intersection of creases and lines. Unlike minutiae, such points can still be extracted even on low resolution palmprints. Matching is carried out using an SVD factorisation of a proximity matrix and takes account of the coordinates of the detected points and their local texture. Our experiments have yielded some very good results evidenced by an EER of 0.10%.

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