Abstract:

In order to improve the rate of face detection under complex background and reduce detection time，we propose a face detection algorithm based on skin color segmentation and improved Haar features. First we derive the probability of every bit of skin color by elliptical skin color model and logistic regression analysis in YCbCr color space and generate the skin probability diagram, which will map every bit of pixel values to ［0, 1］.  Then we define the threshold of skin color segmentation to segment the face region rapidly, using parallel genetic algorithm based the Ostu method. Finally combining the SVM training and classification method, we adopt a few Haar variance characteristics instead of the original Haar features to verify the segmented face region. Experimental results show that the proposed method can improve the accuracy of face detection with a fast speed.

Key words: skin color segmentation;elliptical skin color model;regression analysis；genetic algorithm;Haar variance characteristics