Gender Classification Using Local Directional Pattern (LDP)

Abstract

In this paper, we present a novel texture descriptor Local Directional Pattern (LDP) to represent facial image for gender classification. The face area is divided into small regions, from which LDP histograms are extracted and concatenated into a single vector to efficiently represent the face image. The classification is performed by using support vector machines (SVMs), which had been shown to be superior to traditional pattern classifiers in gender classification problem. Experimental results show the superiority of the proposed method on the images collected from FERET face database and achieved 95.05% accuracy.