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
INFOS '16