1. A method for face recognition and identification, the method comprising: receiving at least one probe face image and at least one gallery face image of a subject to be identified, wherein the at least one probe face image is a real-time image and the at least one gallery face image is an image from a pre-existing image database and not a real-time image; preprocessing the at least one probe face image and the at least one gallery face image; normalizing the at least one probe face image and the at least one gallery face image to obtain a consistent dynamic image range, wherein the at least one probe face image is a thermal image or a visible face image and wherein the at least one gallery face images is a thermal face image or a visible face image; creating at least one set of face patterns comprising face pattern words (FPWs) or face pattern bytes (FPBs) using at least one set of Gabor wavelet transform (GWT) coefficients with each probe face image and gallery face image, wherein the creation of FPWs comprises the maximal magnitude of the GWT coefficients and wherein the creation of FPBs comprises the maximal magnitude of the GWT coefficients; calculating the Hamming Distance between the at least one probe face image and the at least one gallery face image using the FPWs or FPBs and a face mask, wherein the face mask in the calculation of the Hamming Distance is used to minimize or to eliminate non-face image distractions; and identifying a subject by using the Hamming Distance calculated from FPWs or FPBs, wherein the method utilizes at least one processor for receiving, preprocessing, and normalizing the images, for creating the at least one set of face patterns comprising the FPWs or FPBs, for calculating the Hamming Distance, and for identifying a subject.