Face Recognition Based On Gabor Wavelet Transform

Identifying a human individual from his or her face is one of the most important methods in status certification, and is the research focus in applied mathematics,pattern recognition and artificial intelligence.This thesis uses Gabor wavelet transform to research face recognition. The algorithms needs examples of what the landmark jets look like to locate the landmarks in novel image, which is described as:choose many different Gabor jets of every landmark in novel image, and use the average grid which is constructed by grid structure edge of different styles of face graph to characterize the face geometric features. To calculate the similarity of two face graph, the algorithm first finds landmark locations on the images that correspond to facial features such as the eyes, nose, and mouth. It then uses Gabor wavelet convolutions at these points to describe the features of the landmark, which is used to construct the face graph. The face graph nodes are placed at the landmark locations, and each node contains a Gabor jet extracted from that location. A face graph is used to represent each image. The similarity of two images is a function of the corresponding face graphs. The main work and contribution of the dissertation are as follows:(1) The commonly used face recognition theories and methods are summarized compendiously in this dissertation. The research actualities and technology development of current face recognition technology are discussed based on a series of international face recognition evaluations which were conducted in recent years.(2) Two-dimensional Gabor wavelets transform and its response characteristics in recognition applications are researched. Two-dimensional Gabor wavelets transform is realized by the convolutions of a bank of two-dimensional Gabor filters and the gray values of pixels in an image around a given position in an image. In this dissertation, it is validated by the computational results that the local features of face images can be represented through selecting the parameters of Gabor filters.(3) The preprocessing of face image is researched. The aim of face image preprocessing is to regularize the face image which is captured by image collecting devices to normalized image, it includes three steps mainly:face detection and eye location, geometry normalization, gray value normalization. (4) The basic processes of the two-dimensional Gabor wavelets transform based face recognition are researched. The similarity functions are also analyzed.(5) The algorithm is validated by the experiment results.