Research On Face Recognition Of Infrared Image

Because of portability, economic and accurately of the recognition, furthermore, the face recognition technology has the features of intuition, passivity and non-infringe , which makes it one of the hot spots of the pattern recognition. The important feature of face recognition through infrared image of face is that infrared image of face being composed of infrared radiation of structure of the skin , it is independent of external light. Also the infrared image is in connection with vascularity of the face, which is unique, strong in anti-interference performance and anti-fraud. So more and more attentions are payed on this field.In this paper, firstly the character and eigenvector were extracted of the infrared image of face, the eigenvector was collected through the intersection point of the blood vessel of the infrared image of face, moreover the infrared image of face was matched by eigenvectors. Secondly the partition of the infrared image of face was studied based on mixed Gaussian distribution. The infrared image of face was divided to segment of face and background by hand based on Bayes algorithm of division of face with minimum error rate, supposing these two parts obey different Gaussian distribution. Parameters of Gaussian distribution were initialized through EM algorithm separately, so the probability distributions of segment of face and background were obtained. the eigenvector were extracted on smoothing filtering of image of face by anisotropic diffusing filter, contrast was strengthened on the fringe of blood vessel of face, then the blood vessel in the infrared image of face was achieved through top-hat segmentation. In the end, infrared image was recognized by the eigenvector matching algorithm. Validated by the database algorithm, the algorithm suggested in this paper has a high recognition rate and feasibility.