Traditional Chinese medicine tongue color and fur color quantitative analysis method based on machine learning

Abstract

The invention relates to tongue color and fur color identification. The invention, and particularly relates to a traditional Chinese medicine tongue color and fur color quantitative analysis method based on machine learning. The method includes carrying out tTongue image investigation and image acquisition are carried out on crowds of different regions and ages; tongue color and moss color judgment is carried out on the collected tongue image through a consistent review method; constructing traditional Chinese medicine tongue image big data; extracting a tongue body area from the tongue imageimage in the traditional Chinese medicine tongue image big data; carrying out HSV space clustering; the method comprises the following steps: firstly, dividing a tongue color image into sub-images, automatically generating a tongue color color card and a fur color card according to a clustering result by tone, constructing a pixel color attribute classifier X based on an xgboost machine learning algorithm, and respectively constructing a whole tongue color classification model s and a whole tongue fur color classification model t based on the xgboost machine learning algorithm; the technical scheme provided by the invention can effectively overcome the defects that the recognition result is low in accuracy and depends on sample data in the prior art.

Description

technical field [0001] The invention relates to identification of tongue color and fur color, in particular to a machine learning-based quantitative analysis method for tongue color and fur color in traditional Chinese medicine. Background technique [0002] Traditional tongue inspection is mainly based on naked eye observation, and its accuracy depends on the doctor's experience, limited by environmental factors, lack of objective and unified identification indicators, and cannot meet the reproducibility requirements in research. Doctors may make mistakes in judging tongue color and fur color due to factors such as light and environment. Therefore, it is urgent to use machine quantitative analysis and identification methods. There are mainly two methods in the prior art: [0003] Convolutional Neural Network Classification Model [0004] Directly use the neural network to classify and distinguish the color of the tongue coating. Taking the InceptionV4 classification netwo...

AI Technical Summary

Problems solved by technology

The above method is indeed improved compared with the first method, but there are also problems. For example, using the sliding window method to take blocks is random and unstable. Often a picture has many other colors, which leads to deviations in marking, resulting in the final inaccurate result

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