A V-Hog tensor based discriminant analysis for small size face recognition

Abstract

Apart from Illumination, Pose and Expression variations, low dimension is also a primary concern that spiflicate the performance of face recognition system. This work distils to applying v-Hog Tensor discriminant analysis on small sized face image to yield good result in terms of correctness rate. Firstly the face image is mapped on to w-quintuple Colorspace to effectively interpret information existing in the image. Further discriminant features are extracted out of Tensor plane to bore on the confounded image due to reduction of image size. To exhibit the beauty of the feature, v-Hog [22] is adopted. The obtained features are further mapped to a lower dimension space for efficient face recognition. In this work the effect of fSVD [17] with bias is also considered to fortify the recognition system. Finally, for classification five different similarity measures are used to obtain an average correctness rate.