Face Recognition Based on Sub-image Feature Extraction and LS-SVM

Author

Zhang, Xinming ; Zou, Jian

Author_Institution

Coll. of Comput. & Inf. Technol., Henan Normal Univ., Xinxiang

Volume

1

fYear

2008

fDate

12-14 Dec. 2008

Firstpage

772

Lastpage

775

Abstract

Based on sub-image feature extraction method of face images and least square support vector machine (LS-SVM) classifier, a face recognition model is proposed. In this model, face images are divided into sub-images firstly, then the discrete cosine transform is operated on each sub-image and the optimal coefficients are selected to denote the sub-image, and combine them into a single feature vector of the whole face image, finally LS-SVM is employed as a classifier with its optimized parameters. On ORL face database, experimental results show the proposed method is effective and has fast recognition speed.

Keywords

discrete cosine transforms; face recognition; feature extraction; image classification; least squares approximations; optimisation; support vector machines; discrete cosine transform; face recognition; feature vector; least square support vector machine classifier; optimal coefficient; parameter optimization; subimage feature extraction; Computer science; Discrete cosine transforms; Equations; Face recognition; Feature extraction; Humans; Least squares methods; Support vector machine classification; Support vector machines; Visual system; discrete cosine transform; face recognition; least square support vector machine; sub-image feature;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Software Engineering, 2008 International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-0-7695-3336-0

Type

conf

DOI

10.1109/CSSE.2008.1088

Filename

4721863