1. A method of identifying a human subject by gait recognition, the method comprising: obtaining a number of image frames of the human subject showing the human subject's walking style and storing the image frames in a memory, receiving by circuitry a gait sequence, the gait sequence including a predetermined number of the image frames of the human subject; processing by circuitry, the received gait sequence to generate a gait-energy-image (GEI), wherein the GEI is a sum of walking silhouette images divided by the number of the image frames; computing by circuitry, a plurality of Gabor filter responses by convoluting the generated GEI with a bank of Gabor filters, the filter bank including a first predetermined number of unique scales, and a second predetermined number of unique orientations, partitioning by circuitry, each Gabor filter response of the computed plurality of Gabor filter responses, into a predetermined number of overlapping regions, wherein the partitioning separates the walking silhouette images into moving parts of the human subject selected from the group consisting of a head, an arms, a leg and a torso; extracting by circuitry, a predetermined number of statistical features only from the overlapping regions, the extracted statistical features corresponding to texture content of the subject; and identifying by circuitry, the human subject based on a classification of the extracted statistical features.