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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.

In this paper, a TCM constitution clinical decision support system is introduced. The features, functions, structure and working flow of this system are discussed and illustrated in detail. This system is composed of 5 modules. They are query module, investigation construction module, investigation modification module, investigation deletion module and data analysis module respectively. The property information, constitution information and tongue feature information are collected through investigation construction module. The constitution types of the testers can be automatically recognized and the prescriptions related to specific constitutions are automatically produced. Through data analysis module, specificities and sensitivities between the specific constitutions and the tongue features can be automatically obtained. The implementation of this system is of important value and guiding function during the process of TCM clinical diagnoses and treatments.

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.

To optimize the extracting condition of fatty constituents from Tabanus bivittatus and analyse by GC-MS.Taking fatty yield as index, the extraction technology parameters of fatty constituents of Tabanus bivittatus ere optimized by single factor test and orthogonal test.The optimum extraction parameters were as follows: the ratio of acetone to petroleum ether 1: 2, extraction time 2 h, solid-liquid ratio 1: 50. Twenty-one fatty acids were identified by GC-MS.The process is reasonable and with good reproducibility. The main components of fatty acids in Tabanus bivittatus are palmitoleic acid, palmitic acid, linoleic acid, oleic acid and stearic acid.