Color Face Detection Algorithm In The Complex Context Of Realization

Research efforts in face processing include face detection, face tracking, face recognition as well as derivative analysis of pose and expression. Face detection is a key technology of the filed of face information processing. In the beginning, research efforts in face processing chiefly fastened its attention on face recognition, and early face recognition algorithms are based on having a frontal face or faces'getting easily. But with faces'application spreading and practical systems'demand improving, this kind of research on this condition can't satisfy requirements any more. Face detection develops as an alone research. In this dissertation, we first sum up and analyze current typical algorithms on face detection, and then present a multistage detection and conformed method from coarse to fine in order to find faces in the complicated background. This method is discussed on details as follows. First, the algorithm analyzes and compares complexion's clustering in the different color space, and then establishes a skin model based on the color space of YCbCr. Using this model, the complexion is segmented and two-value processed. On account of noise's immanence, we can get backup face area using the filter based on mathematical morphology. In the selective and conformed stage, we utilize faces'geometrical characters to roughly choose between these backup areas. Finally we use Euler number and fair model to repeatedly choose and verify these regions, and to get the end results. The algorithm, because of using the skin model that decreases backup regions under the complicated background, is faster than the ones based on neural network (NN), supported vector machine (SVM), model matching and so on. But skin model is easily influenced by the light, so we present the method of using "Gray World"to judge whether color warp exists in an image. If it is existent, we adopt the method of "Reference White"to process lighting compensation. By lighting compensation processing, the algorithm based on the skin model gets improving and decreases the missing rate (MR). In the last part of the dissertation, we implement the algorithm using Visual C++, and experiment in our face testing set. The results show that our method is robust, and strongly adaptive to variant pose, different illumination and ages. But due to face's...