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Conference Paper
Face Recognition Based on Sparse Representation Classifier with Gabor-Edge Components Histogram
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- Authors
- Hansung Lee, Yunsu Chung, Jang-Hee Yoo, Chulho Won
- Issue Date
- 2012-11
- Citation
- International Conference on Signal Image Technology and Internet Based Systems (SITIS) 2012, pp.105-109
- Language
- English
- Type
- Conference Paper
- Abstract
- We describe a new method for recognizing humans by their face, which is robust to the variations of facial imaging conditions, with high accuracy. The human face recognition system consists of three components: i) a new face descriptor based on edge component histogram and its variance between pixels; ii) Gabor-edge components histogram for facial image representation, combining the Gabor wavelet and the proposed edge components histogram; iii) a sparse representation classifier for the face recognition. The effective and robust face recognition with high accuracy is achieved by the Gabor-edge components histogram and the sparse representation classifier. In experiments, higher face recognition performances, which are 99.45% on ETRI database and 99.41% on XM2VTS database, have been achieved. © 2012 IEEE.