Tongue's substance and coating recognition analysis using HSV color threshold in tongue diagnosis

In ISO TC249 conference, tongue diagnosis has been one of the most active research and their objectifications has become significant with the help of numerous statistical and machine learning algorithm. Color information of substance or tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. In order to produce high reproducibility of color measurement analysis, tongue images have to undergo several procedures such as color correction, segmentation and tongue’s substance-coating separation. This paper presents a novel method to recognize substance and coating from tongue images and eliminate the tongue coating for accurate substance color measurement for diagnosis. By utilizing Hue, Saturation, Value (HSV) color space, new color-brightness threshold parameters have been devised to improve the efficiency of tongue’s substance and coating separation procedures and eliminate shadows. The algorithm offers fast processing time around 0.98 seconds for 60,000 pixels tongue image. The successful tongue’s substance and coating separation rate reported is 90% compared to the labelled data verified by the practitioners. Using 300 tongue images, the substance Lab color measurement with small standard deviation had revealed the effectiveness of this proposed method in computerized tongue diagnosis system.