의료자산보호에서 얼굴인식을 위한 가보 웨이블릿 분석

Abstract

Medical asset protection is important in each medical institution especially because of the law on private medical record protection and face recognition for this protection is one of the most interesting and challenging problems. In recognizing human faces, the distortion of face images can be caused by the change of pose, illumination, expressions and scale. It is difficult to recognize faces due to the locations of lights and the directions of lights. In order to overcome those problems, this paper presents an analysis of coefficients of Gabor wavelets, kernel decision, feature point, size of kernel, for face recognition in CCTV surveillance. The proposed method consists of analyses. The first analysis is to select of the kernel from images, the second is an coefficient analysis for kernel sizes and the last is the measure of changes in garbo kernel sizes according to the change of image sizes. Face recognitions are processed using the coefficients of experiment results and success rate is 97.3%. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved in the face recognition area.