Face recognition using improved fast PCA algorithm

被引：14
|
作者：
Neerja [1 ]
Walia, Ekta [2 ]
机构：
[1] Rayat & Bahra Inst Engg & BioTech, PIN 140104, Mohali, Punjab, India
[2] Punjabi Univ, Dept Comp Sci, Patiala, Punjab, India
来源：
CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 1, PROCEEDINGS | 2008年
关键词：
face recognition; fuzzy feature extraction; eigenface; Principle Component Analysis;
D O I：
10.1109/CISP.2008.144
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：
The Principal Component Analysis (PCA) is one of the most successful techniques that have been used to recognize faces in images. However, high computational cost and dimensionality is a major problem of this technique. There is evidence that PCA can outperform over many other techniques when the size of the database is small. In this paper, a fast PCA based Face Recognition Algorithm is proposed. In the proposed algorithm the database is sub grouped using some features of interest in faces. Only one of the obtained subgroups is provided to PCA for recognition. The performance of the proposed algorithm is tested on Indian face database, and the obtained results show an improvement in performance of the proposed algorithm as compared to the same with PICA method.
引用
收藏
页码：554 / +
页数：3
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