Neural Network based Face Recognition with Gabor Filters

Gabor-based face representation has achieved enormous success in face recognition. This research addresses a hybrid neural network solution for face recognition trained with Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. The neural network employed for face recognition is based on BAM for dimensional reduction and multi-layer perception with backpropagation algorithm for training the Gabor features. The effectiveness of the algorithm has been justified over a face database with images captured at different illumination conditions.

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