Palmprint Recognition Using Kernel PCA of Gabor Features

被引：0

作者：

Ekinci, Murat ^{[1
]}

Aykut, Murat ^{[1
]}

机构：

[1] Karadeniz Tech Univ, Dept Comp Engn, Comp Vis & Pattern Recognit Lab, TR-62080 Trabzon, Turkey

来源：

23RD INTERNATIONAL SYMPOSIUM ON COMPUTER AND INFORMATION SCIENCES | 2008年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a new method for automatic palmprint recognition based on kernel PCA method by integrating the Gabor wavelet representation of palm images. Gabor wavelets are first applied to derive desirable palmprint features. The Gabor transformed palm images exhibit strong characteristics of spatial locality, scale, and-orientation selectivity. These images can produce salient features that are most suitable for palmprint recognition. The kernel PCA method then nonlinearly maps the Gabor-wavelet image into a high-dimensional feature space. The proposed algorithm has been successfully tested on two different public data sets from the PolyU palmprint databases for which the samples were collected in two different sessions.

引用

页码：106 / +

页数：2

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