The Research Of Face Detection Based On Skin Color And Support Vector Machine

Face detection is a technique to detect human faces in a picture and use certain strategy to label its location, size and position. It is the first one to solve in many human faces information processing domain. It is essential to realize the automatic person face recognition system.It is more than 20 years about the research for person face detection; so far, because of the complexity of person face detection itself, there hasn't been a method can solve it totally. People started to think about it from different ways, and considering the fusion of many different methods, all these had obtained quite well results. A great amount of literatures, surveys and research papers concerning up-to-date techniques of face detection and face recognition are read and analyzed. Some hot issues about face detection are discussed. A face detection system about color images is built up. The research work of this paper mainly includes the following four aspects:(1) It has realized a skin region division algorithm based on the YCbCr color space. In view of the traditional skin color model, I have made some improvements; it has enhanced the detection speed efficiently without affecting the result which is advantageous to the realization of real-time person face detection system.(2) I have used the traditional valve value division thought in skin color region processing. To the same image, one kind of time sharing dynamic valve value division algorithm has been used. It can effectively separate the different skin color region and the skin color region from the background in the basis of detect out every skin region; To the different images, one kind of overall situation dynamic valve value division algorithm has been used. This method can adapt to all kinds of different sizes of person faces in the same or different images very well.(3) It has realized the fine detection and localization of person face based on the support vector machine (SVM) method. This method is used based on the skin color division pretreatment; correspondingly I have adjusted its realization strategy which can effectively solve the speed problem. (4) In the sample selection aspect, I have not adopted the traditional method which based on the gradation image sample. I chose face and non-face sample based on the 20x20 two values images with pretreatment to train SVM. The test result indicated this improvement greatly enhanced the detection speed.(5) How to gradate the images which are used to select features are not directly come from the luminance component alone but from the color information also. The test result indicated that this method is better than the way using luminance information alone or the chroma information alone.Face detection and localization is a highly practical application. The particular demand of application must be taken enough attention on the process of detection and localization of human face, which is such a complicated high-dimension pattern. Integrated methods are frequently employed to achieve the accuracy and real-time ability of the system.