and DCT for dimensionality reduction. The algorithm is based on a genetic algorithm to
improve the selection of training set of images for the PCA algorithm. Genetic algorithm
helps to select the images, which best represent each gender, from the image database. We
have evaluated a nearest neighbor classifier as well as a neural network. Experimental
results show a correct identification rate of 85, 9%.