Graph theory-based Chinese medicinal tongue nature and tongue coat separation algorithm

Abstract

The invention discloses a graph theory-based Chinese medicinal tongue nature and tongue coat separation algorithm, which comprises the following steps of: converting an acquired tongue image into a hue, saturation and value (HSV) model, and dividing a tongue coat initial segmentation area by using an H value; dividing the tongue image into a set of areas; forming an initial segmentation result by using the initial segmentation area and an independent vertex in the image; sequentially stacking differences among area combination operator calculation areas; when valid elements are in the stack, separating the areas if the difference of the stack top areas is greater than one of the internal differences of two areas, determining that the stack top elements are invalid, repeating the step, otherwise, merging the two areas, and deleting the stack top elements and the differences between the related areas of the two areas; and calculating related contents of the newly merged areas, stacking the differences among the areas, and resetting the invalid elements in effect. According to the characteristic of the H value of the HSV space, the tongue coat initial segmentation area is determined, and segmentation efficiency and precision of the algorithm are improved; a threshold function adaptive algorithm is constructed, and the nature and coat crossing detail distinguishing capacity of the algorithm is improved; and the iterative algorithm of the segmentation process is improved by using area combination operators, and smooth nature and coat transition areas are segmented according to the human eye perceptiveness.

Description

Technical field [0001] The invention belongs to the technical field of general image data processing or generation, and particularly relates to a traditional Chinese medicine tongue quality and tongue coating separation algorithm based on graph theory. Background technique [0002] The information contained in tongue quality and tongue coating is an important diagnostic basis for the objectification of tongue diagnosis in Chinese medicine. Before quantitative analysis of tongue quality and tongue coating, it is necessary to separate the tongue quality and tongue coating from the tongue image. The quality of the separation effect is related to the success or failure of the computer inferring the pathology or symptom type. In the early tongue diagnosis system, the tongue texture and the tongue coating are often separated manually, that is, the user of the system selects an area from the tongue image and marks this area as the tongue texture or tongue coating. [0003] There are many...

AI Technical Summary

Problems solved by technology

[0006] The technical problem solved by the present invention is that although the algorithm of the prior art abandons the limitation of incomplete separation when manually separating the tongue mass and tongue coating, there is still the problem that the calculation speed cannot be guaranteed while accurately separating the tongue mass and tongue coating , and the algorithm is not standardized, and after solving some problems, it brings new problems, and then provides an optimized TCM tongue quality and tongue coating separation algorithm based on graph theory

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