International Journal of Scientific Engineering and Research (IJSER)
Gender classification is an important matter for Human Computer Interaction devices. A new methodology for gender classification is examined in this study where the facial feature is extracted from local region of a face using gray color intensity. The facial area is divided into eighty one equal sized square sub regions and Local Minima Pattern (LMnP) method is applied to each pixel. LMnP histograms extracted from those regions are concatenated into a single vector to represent that particular face. The classification accuracy obtained using Local Minima Pattern (LMnP) along with support vector machine as a classifier has outperformed all traditional feature descriptors for gender classification. It is evaluated on the images collected from popular FERET database