Gender identification from face images

In this study, an approach is developed for automatic gender classification from human face images. For representing the face images, different kinds of feature extraction methods (Local Binary Pattern operator, Gabor filtering, Local Gabor Binary Pattern operator) are used. The feature vectors are tested with AdaBoost and Support Vector Machine (SVM) algorithms. The experiments conducted on the face images from the MORPH database show that our method outperforms the current state of the art methods.