Tongue image segmentation method based on color decomposition and threshold technology

Abstract

The invention provides a tongue image segmentation method based on color decomposition and the threshold technology. The method comprises steps that S1, a tone component of a tongue image in the HSI color space is transformed, and tone components of a tongue and an upper lip after transformation and the neighbor tissue are made to have tone difference; S2, image threshold segmentation of the transformed tone component is carried out to obtain the binary segmentation result, after morphological operation of the binary segmentation result is carried out, the initial tongue region containing thetrue tongue and the upper lip is extracted; and S3, the initial tongue region is corrected, two image threshold segmentation methods are selected, one of segmentation results of the two image threshold segmentation methods is utilized to separate the true tongue region from the upper lip region, and the final segmentation result of the tongue image is obtained. The method is advantaged in that themethod is simple and effective, and image segmentation performance is substantially improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a tongue image segmentation method based on color decomposition and threshold technology. Background technique [0002] Tongue diagnosis is one of the main contents of "inspection" in traditional Chinese medicine, and it is one of the traditional diagnostic methods with Chinese characteristics. Tongue image is the most sensitive index to reflect the physiological function and pathological changes of the human body, and it has important application value in the process of diagnosis and treatment of traditional Chinese medicine. Applying image processing technology to establish an objective quantification and recognition method for tongue diagnosis information and realize the automation of TCM tongue diagnosis has important practical significance for the modernization of TCM. In the automatic tongue diagnosis system, after the patient's tongue image is acquire...

AI Technical Summary

Problems solved by technology

The DGF method fails to completely overcome the limitations of the C2G2F method, and the segmentation accuracy and stability need to be improved

[0006] In addition, the above tongue image segmentation methods based on active contour models have a common defect, that is, they are all sensitive to the initial contour

Once the initial contour contains non-tongue strong edges from adjacent tissues of the tongue such as the neck, face, lips, etc., it is difficult for the above-mentioned tongue image segmentation method based on the active contour model to converge to the real tongue contour

[0007] In summary, the existing tongue image segmentation methods have certain limitations, and the segmentation effect needs to be further improved

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