Paper Title
Gender Classification From Face Images With Local Texture Pattern

Recognizing human gender automatically by a computer is a challenging problem. It has been attracting research attention due to its wide real-life applications. Gender classification can be viewed as an essential preprocessing step in face recognition. Because human faces contain a lot of really useful information, many approaches based on facial features have been investigated for gender classification. In this paper, we present a novel texture pattern as feature descriptor to identify the gender from the facial images. The classification is performed by using a support vector machine. Experimental results on the FERET database are provided to illustrate the proposed approach is an effective method, compared to other similar methods. Keywords- Gender Classification, Local Texture Pattern, Support Vector Machine