Ensemble Incomplete Wavelet Packet Subspaces for Face Recognition Based on Fuzzy Integral
ZHAI Jun-Hai1, WANG Xi-Zhao1, ZHANG Su-Fang2
1.Key Laboratory of Machine Learning and Computational Intelligence, School of Mathematics and Computer Science, Hebei University, Baoding 071002 2.Teaching and Research Section of Mathematics, Hebei Information Engineering School, Baoding 071000
Abstract An ensemble incomplete wavelet packet subspaces method based on fuzzy integral for face recognition is proposed, and it is compared with 5 related approaches. Firstly, face images are decomposed into different sub-images with incomplete wavelet packet transform. For sub-images with low frequency information in two directions, features are extracted directly. And for high frequency sub-images with low frequency information in one direction, features are extracted after these images are averaged. Next, fuzzy classifiers are trained by the obtained wavelet subspace images. Finally, the trained classifiers are integrated by fuzzy integral. The proposed method makes full use of the information provided by sub-images with different frequency and improves the accuracy of face recognition. The experimental results on ORL, YALE, JAFFE and FERET show that the proposed method has higher accuracy than 5 related approaches.
ZHAI Jun-Hai,WANG Xi-Zhao,ZHANG Su-Fang. Ensemble Incomplete Wavelet Packet Subspaces for Face Recognition Based on Fuzzy Integral[J]. , 2014, 27(9): 794-801.
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