Complex kernel PCA for multimodal biometric recognition

被引：3

作者：

Wang, Zhifang ^{[1
]}

Han, Qi ^{[1
]}

Niu, Xiamu ^{[1
]}

机构：

[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150006, Peoples R China

来源：

IEICE ELECTRONICS EXPRESS | 2009年 / 6卷 / 16期

关键词：

multimodal biometric recognition; feature fusion; complex field; FUSION;

D O I：

10.1587/elex.6.1131

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This letter presents a novel multimodal biometric recognition algorithm based on complex kernel principle component analysis (CKPCA). CKPCA generalizes kernel principle component analysis (KPCA) method for complex field to perform feature fusion and classification. Iris and face are used as two distinct biometric modals to test our algorithm. Experimental results show that the proposed algorithm achieves much better performance than other conventional multimodal biometric algorithms.

引用

页码：1131 / 1136

页数：6

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