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Method for automatic tongue coating segmentation based on deep learning

A technology of deep learning and automatic segmentation, which is applied in image analysis, image data processing, instruments, etc., can solve the problem of low accuracy of tongue coating segmentation, and achieve the effect of high accuracy and wide application range

Active Publication Date: 2018-01-19
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides an automatic tongue coating segmentation method based on deep learning. The deep learning method based on big data can realize more accurate tongue coating segmentation, which solves the problem of the accuracy of tongue coating segmentation in existing methods. low problem

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  • Method for automatic tongue coating segmentation based on deep learning
  • Method for automatic tongue coating segmentation based on deep learning
  • Method for automatic tongue coating segmentation based on deep learning

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Embodiment Construction

[0030] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be further described in detail below in conjunction with the drawings and specific embodiments.

[0031] like figure 1 As shown, the present invention provides a method for automatic tongue coating segmentation based on deep learning, including five major steps:

[0032] Step (1) Collecting the tongue coating image through a camera, etc., as the input tongue coating image;

[0033] Step (2) using the deep learning method Faster R-CNN to realize tongue coating detection, and automatically obtain preliminary tongue coating area images;

[0034] Step (3) using the deep learning method VGG-16 to realize the automatic calibration of the tongue coating area image to obtain a more accurate tongue coating area image;

[0035] Step (4) Automatically segment the tongue coating area image...

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Abstract

The invention discloses a method for automatic tongue coating segmentation based on deep learning. The method comprises the steps of S1, collecting and inputting an image comprising a tongue coating;S2, for the image including the tongue coating, adopting a Faster R-CNN deep learning method for tongue coating detection, and automatically obtaining a preliminary tongue coating region image; S3, calibrating the preliminary tongue coating region image with a VGG deep learning method to obtain a more accurate tongue coating region image; and S4, automatically segmenting a tongue coating image according to the calibrated tongue coating region image. The method in the invention realizes the more accurate tongue coating segmentation based on the deep learning method of big data, and solves the problem that the existing method has low accuracy of tongue coating segmentation.

Description

technical field [0001] The invention relates to the application of computer vision, image processing and artificial intelligence in the health field of traditional Chinese medicine, in particular to an automatic tongue coating segmentation method based on deep learning. Background technique [0002] The tongue coating contains a lot of information about human body constitution, which means that the type of human body constitution can be judged objectively by observing the tongue coating. However, this requires rich professional experience of Chinese medicine experts, and it is even more difficult for ordinary doctors and ordinary people. Therefore, artificial intelligence is used It is very important to realize the automatic analysis of tongue coating with technology, but the premise of automation is to realize the automatic segmentation of tongue coating from facial images containing tongue coating, and the current segmentation accuracy is low. [0003] Tongue coating segme...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06T7/60
Inventor 文贵华曾海彬马佳炯
Owner SOUTH CHINA UNIV OF TECH
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