Performance Evaluation of Gabor Wavelet Features for Face Representation and Recognition

The choice of the object representation is crucial for an effective performance of cognitive tasks such as object recognition, fixation, etc. Face recognition is an example of advanced pattern recognition. The main aim is to investigate alternative methods to be used for face recognition, in particular the use of wavelets. The representation of images by Gabor wavelets is chosen for its biological relevance and technical properties. The Gabor wavelets are of similar shape as the receptive fields of simple cells in the primary visual cortex (V1). In the proposed work, use of Gabor wavelets for efficient face representation is demonstrated. Face recognition is influenced by several factors such as shape, reflectance, pose, occlusion and illumination which make it even more difficult. The present work introduces the Gabor wavelets for an efficient face recognition system simulating human perception of objects and faces. The system is tested for the standard database like YALE, JAFFE, ORL and FEI. Experimental results show the effectiveness of the proposed system. Thus Gabor wavelet approach provides a better representation and achieves lower error rates.