A Mean Features Method for Face Photo-Sketch Synthesis and Recognition

Converting a photo image to sketch, or conversely, is an essential step in face-sketch recognition. In this paper, we propose an efficient mean feature method to synthesize a sketch from a photo and vice versa. The main idea is to map a photo to the same sketch texture and vice versa. This is done by generating a mean features image from the training set. We used pseudo-sketch to sketch recognition as a performance measure for the proposed method. SIFT feature and Euclidean distance are used in the recognition step. We used CUHK viewed-sketch and PRIP-HDC forensic sketch databases in our experiments. Also, comparisons with state-of-the-art methods are presented. Experimental results for the CUHK database showed that the proposed method outperform some state-of-the-art method. We obtained a recognition rate of 96% at rank 1, which is better than some of the state-of-the-art methods. Our results for the PRIP-HDC database show improvement in the recognition rate from 34% to 57% at rank 50