An efficient method of face recognition by fusing original and diagonal images

Image level fusion combines an image in different ways with its original version so that the combine image may contain more relevant information than the original one. This paper presents a novel method for face recognition by fusing original and corresponding diagonal images. Two ways of image fusion technique have been performed here. Firstly, we generate diagonal face image from original face image and append original image with the diagonal image horizontally side by side. Secondly, original face image and the corresponding diagonal face image are appended vertically to get two sets of fused image matrices. The G-2DFLD method is applied on both of these large fused images for extraction of discriminant features, which integrate the underlying discriminant information along the horizontal, vertical and diagonal directions. This extracted feature matrices are applied on Radial Basis Function-Neural Networks (RBF-NN) for classification and recognition. Experiments on the AT&T face database (formally known as ORL database) indicate the superiority of the proposed method as compared to some of the conventional methods.