Feature Facial Image Recognition Using VQ Histogram in the DCT Domain

被引：1

作者：

Chen, Qiu ^{[1
]}

Kotani, Koji ^{[2
]}

Lee, Feifei ^{[1
]}

Ohmi, Tadahiro ^{[1
]}

机构：

[1] Tohoku Univ, New Ind Creat Hatchery Ctr, Aoba Ku, 6-6-10 Aza Aoba, Sendai, Miyagi 9808579, Japan

[2] Tohoku Univ, Grad Sch Engn, Dept Elect, Aoba Ku, Sendai, Miyagi 9808579, Japan

来源：

SECOND INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING | 2010年 / 7546卷

关键词：

Face recognition; Vector quantization (VQ); DCT domain; FACE RECOGNITION;

D O I：

10.1117/12.855647

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

In this paper, a novel algorithm using vector quantization (VQ) method for facial image recognition in DCT domain is presented. Firstly, feature vectors of facial image are generated by using DCT (Discrete Cosine transform) coefficients in low frequency domains. Then codevector referred count histogram, which is utilized as a very effective personal feature value, is obtained by Vector Quantization (VQ) processing. Publicly available AT&T database of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions, is used to evaluate the performance of the proposed algorithm. Experimental results show face recognition using proposed feature vector is very efficient. The highest average recognition rate of 94.8% is obtained.

引用

页数：7

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