Performance analysis of different Matrix decomposition methods on Face Recognition

被引：0

作者：

Jagadeesh, H. S. ^{[1
]}

Babu, Suresh K. ^{[2
]}

Raja, K. B. ^{[2
]}

机构：

[1] APSCE, Dept Elect & Commun Engn, Bengaluru, India

[2] UVCE, Dept Elect & Commun Engn, Bengaluru, India

来源：

2016 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI) | 2016年

关键词：

Biometrics; City-block distance; Euclidean distance; Extended directional binary codes; Matrix decomposition;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Applications using face biometric are ubiquitous in various domains. We propose an efficient method using Discrete Wavelet Transform (DWT), Extended Directional Binary codes (EDBC), three matrix decompositions and Singular Value Decomposition (SVD) for face recognition. The combined effect of Schur, Hessenberg and QR matrix decompositions are utilized with existing algorithm. The discrimination power between two different persons is justified using Average Overall Deviation (AOD) parameter. Fused EDBC and SVD features are considered for performance calculation. City-block and Euclidean Distance (ED) measure is used for matching. Performance is improved on YALE, GTAV and ORL face databases compared with existing methods.

引用

页数：6

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