Lip analysis in traditional Chinese medicine

Objective: To design the lip-color features and classification model and provide an automatic, quantitative method based on the lip detection in facial image. Methods: In this paper, We adopted the lip segmentation algorithm based on the three-dimensional mixture Skin Gaussian Model and color classification in SVM to solve this problem. Specifically, we used the GMM based iterations to confirm skin-color pixels that belong to the skin area. In the process of optimization, we extracted two-dimensional GMM with five parameters as the characteristic to obtain the main color and secondary color to extract and classify the features of the 877 lip images. Consequence: The accuracy and stability of classification method was successfully proved. Conclusion: Firstly, We proposed a Skin Gaussian mixture Model that can be used for the robust and accurate segmentation of facial skin in a probabilistic manner. Secondly, we extracted five parameters from the two-dimensional GMM of the a, b component in the laboratory space as the characteristic of each picture. Finally, we classified the lips through the SVM classifier. As for the lips with mixed color, the method we proposed can have a good performance in identifying the secondary colors, thereby improving the identification precision of the image segmentation and color classification of the lip.