Design And Implementation Of Face Recognition System Based On Point Feature Value

Face recognition is becoming a hotspot in the field of pattern recognition and artificial intelligence because of its great application prospect in security verification system, credit card verification, medicine, file management, videoconference, human-computer interaction and system public security.In this paper, we focus on how to extract the "feature" point set from the image, which is called feature-value in this paper. Because the ability of image processing directly determines the accuracy of the location and recognition of the key parts of the face, it occupies an extremely important position in the whole research. The main image processing methods used in this study include Gaussian smoothing, light compensation and equalization histogram.This paper implements the face recognition system for the core processing of the following steps.First of all, the initial process of face recognition, the first to obtain the image of the light compensation operation, optimize the original image.Then, the most likely face region is acquired by the condition of skin color and so on.The human face is determined according to the symmetry of the human eye, and the image is denoised by using the Gaussian smoothing method.Finally, the feature extraction process is performed by localizing the binarization of the threshold value.This paper considers the facial features and color features of human faces. The color features include key color values such as eyes, mouth, skin, etc. The integrated location layout data and the color data are combined to form a point feature which can identify different human faces. The color feature includes the distance between the eyes, the position of the mouth and the coordinates of the center of gravity. The set of these points with feature forms a set of identification flags that identify this face.Experimental results show that the proposed algorithm can improve the accuracy and speed of face recognition and recognition in face recognition.This research adopts C ++ language in the coding process, and adopts the desktop system frame MFC of Microsoft in the framework of the system. Can effectively reduce the coding staff workload, will focus on the face recognition technology research.