Research On Tongue Color Analysis Methods Based On Semi-Supervised Learning

Tongue Diagnosis is one of the most valuable methods in Traditional Chinese Medicine practice, and its compuerization is inevitable with the rapid development of computer science and technology these years. This dissertation is thus focused on advocating the development of computerized Tongue Diagnosis and researching on the methodology of tongue color training and classification.Major contributions of this dissertation include: analyzing the weaknesses of the current tongue color analysis methods; designing the algorithm of pixel-based tongue color classification system; proposing a semi-supervised method for tongue pixels classification; converting a global optimization problem to a dynamically local one, therefore significantly improving the processing speed; proposing an eigenvalue of color ratios and applying it to tongue color classification and the automatic diagnosis of pancreatitis.First of all, the weaknesses of the the current tongue color analysis methods are summarized systemically, based on the reason of which, pixels in the tongue images are selected as the research subjects of the classification. Later, a new medical biometrics algorithm is suggested based on semi-supervised learning with better performance than that of supervised and unsupervised learning methods.Secondly, by combining forward selection and backward selection, distribution model datasets of 12 tongue colors and pixel-based tongue color model are set up with higher quality training samples. Furthurmore, RKNN algorithm is proposed to classify tongue substance and coating color, converting a global optimization problem into a dynamically local one, suitable for the huge number of the pixels. Finally, a 12-dimension color ratio eigenvalue is applied for the whole tongue color classification.Last but not least, training samples and experiment result are analyzed. With the guidance and assistance of TCM specialists, the feasibility and the accuracy of the automatic pancreatitis diagnosis are also justified with a satisfying experiment result.