Application of Boolean Kernel Function SVM in Face Recognition

被引：2

作者：

Cui, Kebin ^{[1
]}

Du, Yingshuag ^{[1
]}

机构：

[1] N China Elect Power Univ, Sch Comp Sci & Technol, Baoding 071003, Peoples R China

来源：

NSWCTC 2009: INTERNATIONAL CONFERENCE ON NETWORKS SECURITY, WIRELESS COMMUNICATIONS AND TRUSTED COMPUTING, VOL 1, PROCEEDINGS | 2009年

关键词：

face recognition; Karhunen-Loeve transform; support vector machines; Boolean kernel function; multi-classification;

D O I：

10.1109/NSWCTC.2009.172

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

SVM based on Boolean kernel function has outstanding performance in classifying, for the problem of face recognition, recognizing strategies based on MDNF and MPDNF Boolean kernel function SVM are Proposed. Firstly, Karhunen-Loeve transform is employed to get the representation basis of face image set, secondly, the extracted characteristics is translated into 0-1 format, thirdly, SVM based Boolean kernel function are used to classify. The face recognition experiments with ORL face databases show that the proposed methods led to significantly better recognition accuracy compared with traditional PCA method and linear SVM, between the proposed methods, the one based on MPDNF Boolean kernel function get better performance.

引用

页码：619 / 622

页数：4

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