A Fuzzy Logic Approach for Gender Recognition from Face Images with Embedded Bandlets

Abstract

Abstract. In this paper we have proposed a gender recognition system through facial images. We have used three different techniques that involve Bandlet Trans-form (a multi-resolution technique), LBP (Local Binary Pattern) and mean to create the feature vectors of the images. To classify the images for gender, we have used fuzzy c mean clustering. SUMS and FERET databases were used for testing. Experimental results have shown that the maximum average accuracy was achieved using SUMS, 97.1% has been achieved using Band-lets and mean technique, Bandlets and whole image LBP has shown 85.13% and Bandlets with blocked based LBP has shown 87.02% average accuracy.