Palmprint and Palm Vein Feature Fusion Recognition Based on BSLDP and Canonical Correlation Analysis

被引:1
作者
Li Xinchun [1 ]
Zhang Chunhua [2 ]
Lin Sen [1 ]
机构
[1] Liaoning Tech Univ, Sch Elect & Informat Engn, Huludao 125105, Liaoning, Peoples R China
[2] Liaoning Tech Univ, Postgrad Coll, Huludao 125105, Liaoning, Peoples R China
关键词
image processing; block strengthened local directional pattern; canonical correlation analysis; equal error rate; non-contact;
D O I
10.3788/LOP55.051012
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
Aiming at the problems of non-contact images acquisition such as blur phenomenon, poor system identification systems and poor recognition effect, a palmprint and palm vein feature fusion recognition method based on block strengthened local directional pattern(BSLDP) and canonical correlation analysis is proposed. Firstly, we improve the traditional local directional pattern(LDP), and proposed the BSLDP algorithm to obtain the texture direction feature of palmprint and palm vein images. Secondly, the palmprint and palm vein feature fusion is realized effectively based on the canonical correlation analysis. Finally, the match identification is realized based on the chi-square distance. The experimental results show that the equal error rate is only 0.63% and 1.21% in the CASIA-M and the self-built non-contact image database. The results indicate that compared with other traditional and newest algorithms, the proposed method can eliminate redundant information, retain accurate feature information of palmprint and palm vein and improve system identification performance.
引用
收藏
页数:9
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