Analysis of performance of palmprint matching with enforced sparsity

Omar Nibouche; Jianmin Jiang; Paul Trundle

doi:10.1016/j.dsp.2011.10.011

Analysis of performance of palmprint matching with enforced sparsity

Omar Nibouche, Jianmin Jiang, Paul Trundle

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

16 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)	348-355
Journal	Digital Signal Processing
Volume	22
Issue number	2
DOIs	https://doi.org/10.1016/j.dsp.2011.10.011
Publication status	Published (in print/issue) - Mar 2012

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10.1016/j.dsp.2011.10.011

http://www.sciencedirect.com/science/article/pii/S1051200411001606

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title = "Analysis of performance of palmprint matching with enforced sparsity",

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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JO - Digital Signal Processing

JF - Digital Signal Processing

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Analysis of performance of palmprint matching with enforced sparsity

Abstract

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