Novel lip segmentation algorithm for traditional Chinese medical inspection diagnosis

Abstract

The invention belongs to the technical field of computer digital image processing and particularly provides a novel lip segmentation algorithm for traditional Chinese medical inspection diagnosis. The novel lip segmentation algorithm comprises the steps of adopting a Haar classifier to conduct face detection on an image including the face to obtain the upper half portion skin image of the face image and using the upper half portion skin image as training data to establish a face skin Gaussian mixture model, calculating a skin probability graph of the lower half face according to the face skin Gaussian mixture model, adopting an iteration method to remove non-lip pixels in the skin probability graph so as to obtain a coarse lip, and performing coarse lip optimization, wherein the coarse lip optimization step includes the sub-steps of establishing Gaussian mixture models for a lip region and a non-lip region in a coarse lip image respectively to obtain a background probability graph of the coarse lip image, adopting an Otsu to conduct binarization processing on the background probability graph and adopting a region growing method and median filtering and 'k-points' methods to perform refinement to obtain a final lip outline. The novel lip segmentation algorithm is a probability model based method, can be used for processing various lip images provided with complicated backgrounds in a self-adaptive mode, and lip segmentation accuracy can be greatly improved.

Description

technical field [0001] The invention belongs to the technical field of computer digital image processing, and in particular relates to a novel lip segmentation algorithm in traditional Chinese medicine inspection. Background technique [0002] In TCM diagnosis, lip diagnosis is an important diagnostic method, which can be used to reflect the health status of human body organs. According to the theory of inspection in traditional Chinese medicine, the color of a person's lips can be used as a symptom or sign to diagnose whether his spleen or stomach is healthy. The more accurately the lips are segmented, the more reliable the diagnosis. For a long time in China, lip analysis was performed by experienced doctors with naked eyes, which is inefficient especially when dealing with a large number of lip images. Therefore, it is very necessary to design an automatic and accurate segmentation of lips from face images. Moreover, lip detection is very important in many applications...

AI Technical Summary

Problems solved by technology

The early segmentation directly in color or grayscale space increased the contrast between the lip area and the surrounding non-lip area through color space transformation, and used the global or local threshold to directly obtain the lip image. Although this method is fast, it has poor adaptability. Can't adapt to diverse lip images and complex backgrounds

Some other classic model-based methods, such as geometric models, active contour models (ie snakes), clustering algorithms (such as fuzzy C-means), level sets, single Gaussian models, etc., have good robustness, but still It is difficult to adapt to various lip images and complex backgrounds, especially when the lip area and non-lip area have similar colors, it is difficult to accurately segment the lips

[0006] In order to solve these problems, the present invention proposes a new lip segmentation algorithm in traditional Chinese medicine inspection, and specifically adopts a method based on a three-dimensional mixed Gaussian skin color model to solve the problem of automatic and accurate lip segmentation

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