Face Recognition Under varying Lighting Conditions and Noise Using Texture Based and SIFT Feature Sets

Abstract Recognizing face images more reliable even under uncontrolled lighting conditions is one of the most important challenges for practical face recognition systems. We tackle this by combining the strengths of robust illumination normalization, local texturebased face representations,multiple feature fusion. Additionally we propose SIFT which is an approach for detecting and extracting local feature descriptors.By combining the results produced from both the above mentioned approaches,we increase the accuracy of recognizing the given image from group image even with difficult lighting conditions and noise