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| Weighted Multiscale and Multiresolution Face Description and Recognition Method |
| ZENG Zhi-Yong1, LIU Shi-Gang2 |
1.Faculty of Software, Fujian Normal University, Fuzhou 350108
2.School of Computer Science, Shaanxi Normal University, Xi'an 710071 |
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Abstract To overcome the effect of different illuminations and expressions on the recognition results of face images, a weighted multiscale and multiresolution face description and recognition method is presented. Multiresolution analysis is firstly employed to decompose a image into subimages, and three low frequence subbands with different scales are selected to construct multi-scale and multi-resolution image sequences. Then, the sign components of gray level difference between central pixel and its neighbors for each image in image sequences are encoded to express the importance of local face structure. Next, the magnitude components of gray level difference between central pixel and its neighbors are used as the weight of local binary pattern. Finally, block-based fisher linear discriminant analysis is utilized to reduce dimensions of the feature descriptor and enhance its discriminative ability. Experimental results on ORL and FERET face databases show that the proposed method gets significant performance improvement.
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Received: 07 November 2012
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2014, Vol. 27 
