关键词: 自适应唇色分离, Adaboost分类器, 矩阵变换

Abstract: For the lip area detection，the method of applying Haar features to train Adaboost classifier can well adapt to kinds of background environment，but can only get the rectangular area，which can not accurately locate the lip area，while the usual lip color separation algorithm can accurately locate the lip area，but has the high dependence on the background environment of images.Based on this，this paper realizes a method that a self-adaptive skin and lip color separation model is established，which can dynamically adjust constant parameters of skin and lip separation algorithm based on the results of applying Haar features to train Adaboost classifier.The model can dynamically acquire distribution range of skin color and lip color，so it can accurately achieve the lip region of kinds of background images，and improve the effectiveness and robustness of lip-reading deletion.Applying the method to deal with 4000 images in GENKI database，it successfully detects lip area and makes curve fit for the edge of the lip region to locate lip.The results show that the method is more effective.

Key words: self-adaptive skin and lip color separation model, Adaboost classifier, matrix transform