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Efficient face recognition using wavelet-based generalized neural network
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DOI：10.1016/j.sigpro.2012.09.012.png)
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Abstract
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This paper presents an efficient face recognition method where enhanced local Gabor binary pattern histogram sequence has been used for efficient face feature extraction and generalized neural network with wavelet as activation function is being used for classification. In this method the face is first decomposed into multiresolution Gabor wavelets the magnitude responses of which are applied to enhanced local binary patterns. The efficiency has been significantly improved by combining two efficient local appearance descriptors named Gabor wavelet and enhanced local binary pattern with generalized neural network. Generalized neural network is a proven technique for pattern recognition and is insensitive to small changes in input data. The proposed method is robust-to-slight variation of imaging conditions and pose variations. Performance comparison with other existing techniques shows that the proposed technique provides better results in terms of false acceptance rate, false rejection rate, equal error rate and time complexity. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Gabor wavelets
Local Gabor binary pattern
Histogram sequence
Generalized neural network
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