Title :
An extended PCA and LDA for color face recognition
Author :
Qiong Kang ; Lingling Peng
Author_Institution :
Sch. of Comput. Sci., Yangtze Univ., Jingzhou, China
Abstract :
In this paper, we propose a new method for color face recognition. We extract the first, second and third channels of each color image and use PCA and LDA to get a score of each channel, then we use a combine scheme to attain a final score and use this final score to classify test samples. In order to check the performance of our method, we conduct experiments on Georgia Tech (GT) color face database, at the same time, we compare our method with PCA and LDA, and experiment results show that our methods take better performance.
Keywords :
face recognition; feature extraction; image colour analysis; principal component analysis; GT color face database; Georgia Tech color face database; LDA; PCA; channel score; color face recognition; color image extraction; linear discriminant analysis; Color; Databases; Face; Face recognition; Image color analysis; Principal component analysis; Training; channel; face recognition; fusion; normalization;
Conference_Titel :
Information Security and Intelligence Control (ISIC), 2012 International Conference on
Conference_Location :
Yunlin
Print_ISBN :
978-1-4673-2587-5
DOI :
10.1109/ISIC.2012.6449777