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Tongue inspection is the main content of four diagnostic methods “observation, auscultation and olfaction, interrogation, palpation” for traditional Chinese medical science. Traditional tongue inspection mainly depends on doctor’s eyesight and subjective observation to diagnose a disease. It lacks objectivity and hinders further development. It is the only tendency to use computer technology to objective and standard tongue inspection. The tongue split out from the face is the premise for tongue objective. This paper introduces a new dual-threshold segmentation algorithm for tongue image base on HIS.

The article analyzed the old tongue deviation analysis method and introduced a new tongue deviation analysis method with auto-correction aiming at the shortcomings in the old method. This method overcomes the shortcoming that the old method utilized area symmetry to extract central axis and we utilizes the method of shape symmetry analysis to improve the accuracy. In comparison experiment, this method is more accurate than the old one and its efficiency is higher than the old one.

In this paper, first detect the edge of the tongue, to obtain the edge of tongue body coordinates. Then split the tongue using a variety of curve fitting function to analysis plumpness and slenderness of tongue, and compare the accuracy of different curve fitting. Finally, classify the fat tongue and thin tongue by using the neural network.