Title :
Wavelet Energy Entropy as a New Feature Extractor for Face Recognition
Author :
Chen, Cunjian ; Zhang, Jiashu
Author_Institution :
Southwestjiaotong Univ., Chengdu
Abstract :
In face recognition, it is important how to select the invariant facial features especially faces with various pose and expression changes. This paper presents wavelet energy entropy as new facial features to recognize faces under various pose and expression changes. Preliminary experiment results on ORL, YALE face databases with different pose and expression changes indicate that the proposed wavelet energy entropy feature face recognition method is fast and effective compared to other tradition algorithms.
Keywords :
entropy; face recognition; feature extraction; wavelet transforms; face expression change; face recognition; feature extractor; invariant facial feature; pose change; wavelet energy entropy; Data mining; Discrete wavelet transforms; Entropy; Face recognition; Facial features; Feature extraction; Image analysis; Wavelet analysis; Wavelet packets; Wavelet transforms;
Conference_Titel :
Image and Graphics, 2007. ICIG 2007. Fourth International Conference on
Conference_Location :
Sichuan
Print_ISBN :
0-7695-2929-1
DOI :
10.1109/ICIG.2007.60