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Neural Networks have been widely used in face recognition as a reliable classifier. In the proposed method, neural network classifier with CSD coefficients is used to speed up the recognition system. The FPGA implementation of the proposed method indicates that the high speed recognition can be achieved by using neural network classifier with CSD coefficients while maintaining good recognition rate.
An efficient method for face recognition which is robust under illumination variations is proposed. The proposed method achieves the illumination invariants based on the reflectance-illumination model. Different high-pass filters have been tested to achieve the reflectance part of the image which is illumination invariant and maximum filter is proposed as the best method for this purpose. The proposed...
In this paper, we propose a wavelet based feature extraction method with a high tolerance to white Gaussian noise. This method is also computationally efficient. Along with an HMM classifier, this method is used for face recognition. High recognition rates in the presence of white Gaussian noises with different variances show this technique as a promising feature extraction method.
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