基于肤色和改进的贝叶斯分类器的人脸检测(2)

信号检测与分析

Multiple face detection based on skin color and

modified Bayes classifier

Abstract

A new multiple face detection method based on skin is proposed, which got the face candidates by the help of skin color and makes use of wavelet express of the images and the principal component analysis (PCA) to get the eigenvectors distinguishing faces and non-faces, and modified Bayes classifier to detect multiple faces of input images. , the parameter of the modified rules, could control detection accuracy and error probability to apply to different application by setting the values of . In addition, after classing, a mosaic template is used to exclude fake faces to ensure high accuracy and low error probability.

Key word: face detection; shin color segmentation; PCA method; Bayesian rule; mosaic template