Evaluation of Face Recognition System Using Support Vector Machine

被引：3

作者：

Sani, Maizura Mohd ^{[1
]}

Ishak, Khairul Anuar ^{[2
]}

Samad, Salina Abdul ^{[2
]}

机构：

[1] Univ Kebangsaan Malaysia, Inst Microengn & Nanoelect, Ukm Bangi 43600, Selangor, Malaysia

[2] Univ Kebangsaan Malaysia, Fac Engn & Built Environm, Dept Elect & Elect Syst Engn, Ukm Bangi 43600, Selangor, Malaysia

来源：

2009 IEEE STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT: SCORED 2009, PROCEEDINGS | 2009年

关键词：

face recognition; Support Vector Machine; multiclass SVM; Principal Component Analysis;

D O I：

10.1109/SCORED.2009.5443223

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：

Face recognition is an interest subject in pattern recognition study for machine learning applications. It is a non-intrusive system which requires minimal participation from user in order to perform identification tasks. In this paper we present a face recognition system based on Support Vector Machine (SVM) which acts as a multiclass classifier. The performance of this system is evaluated using Yale database with various facial expressions and illumination conditions. This method train and test the images with raw image data of 625 features. The result has achieved an encouraging recognition rates compares to Principal Component Analysis method (PCA).

引用

页码：139 / 141

页数：3

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