Research Article
Evaluation of CIE-XYZ System for Face Recognition Using Kernel-PCA
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@INPROCEEDINGS{10.1007/978-3-319-11629-7_20, author={Hala Ebied}, title={Evaluation of CIE-XYZ System for Face Recognition Using Kernel-PCA}, proceedings={Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers}, proceedings_a={SPIT}, year={2014}, month={11}, keywords={face recognition CIE-XYZ color space kernel-PCA}, doi={10.1007/978-3-319-11629-7_20} }- Hala Ebied
Year: 2014
Evaluation of CIE-XYZ System for Face Recognition Using Kernel-PCA
SPIT
Springer
DOI: 10.1007/978-3-319-11629-7_20
Abstract
paper evaluates the performance of face recognition with different CIE color spaces. The XYZ and Lab* color spaces are compared with the gray image (luminance information Y). The face recognition system consists of a feature extraction step and a classification step. The Kernel-PCA is used to construct the feature space. Kernel-PCA is a nonlinear form of Principal Component Analysis (PCA). The k-nearest neighbor classifier with cosine measure is used in the classification step. Experiments using FEI color database with 200 subjects, show that the b* color component can improve the recognition rate.
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