Face Recognition using Gabor Filters

Gabor based face representation has achieved enormous success in face recognition. This paper addresses a novel algorithm for face recognition using neural networks trained by Gabor features. The system is commences on convolving some morphed images of particular face with a series of Gabor filter co-efficient at different scales and orientations. Two novel contributions of this paper are: scaling of RMS contrast, and contribution of morphing as an advancement of image recognition perfection. The neural network employed for face recognition is based on the Multy Layer Perceptron (MLP) architecture with back-propegation algorithm and incorporates the convolution filter response of Gabor jet. The effectiveness of the algorithm has been justified over a morphed facial image database with images captured in different illumination conditions.