Humanface Detection And Recognition In Complex Background

This paper presents a face detection algorithm for color images in complexbackgrounds based on color model. Our method combined the information of skin colorwith the information of regions. In the YCbCr color space, the method computes the skincolor membership of every pixel in the photo. Then it computes the region membershipof every pixel which related to the center of mass, and finally combines the twomemberships above together to get the face membership.In the section of preprocessing, special methods to enhance the contrast betweenface features and face skin and a local thresholding method were employed so that theresult of the preprocessing was improved. In the section of image segmentation, theclassical split-merge algorithm was applied, and the result improved by a groupingalgorithm. In the section of face matching, an algorithm using a geometric model basedon eyes and mouth was presented. This results a rapid method of face center extractionbased on skin segmentation and human body geometry characteristic is proposed.This paper try to presents a face detection method that can be applied to real-timevideo-based security system, and at the same time, in order to de-noise more effectivelyand quickly, several general de-noising methods and theories are studied in the paper.Compared the methods through, then, the advantage and disadvantage of each method arepointed out and The novel methods are suggested wavelet de-noising.In the end, this paper probed into the advantages and disadvantages of thealgorithms, and put forward suggestions to future work.