Tongue diagnosis method for extraction of effective region and classification of tongue coating

Abstract

In oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of a tongue diagnosis is not only convenient but also non-invasive and widely used in oriental medicine. However, a tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmentation, detecting positions with a local minimum over shading from the structure of a tongue, correcting local minima or detecting edge with color difference, and smoothing edges, where preprocessing performs downsampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue, and then decomposes the color components of the region into hue, saturation and brightness, resulting in segmenting the regions of tongue coatings and classifying them. Finally, a tongue is segmented from a face image and classified into kinds of coatings and substance with a tongue from a digital tongue diagnosis system. The results illustrate the segmented region to include effective information, excluding a non-tongue region and the accurate diagnosis of coatings. It can be used to make an objective and standardized diagnosis.