Abstract
Although machine learning has been the hotpoint in the computer-aided Traditional Chinese Medicine (TCM) tongue diagnosis, it has some inherent disadvantages. For example, tongue image data are always insufficient as a result of no two identical tongues; the images have to be labeled manually, which involve subjectivity and randomness. Therefore, it is still necessary to improve the tongue diagnosis methods based on image processing technology and others. This paper propose a novel and simple tongue body segmentation method based on the RGB model, and then an automatic tongue color classification method is presented on basis of the segmented tongue image. The experimental results show that the tongue segmentation, tongue body & fur separation, and color recognition algorithms proposed in this paper are easy to operate, strong in practicability and high in accuracy.