Chinese medicine tongue color and tongue coating color automatic analysis method based on convolutional neural network

Abstract

The invention provides a Chinese medicine tongue color and tongue coating color automatic analysis method based on a convolutional neural network, belongs to the field of computer vision and the field of Chinese medicine tongue diagnosis, and particularly relates to the technology of deep learning and image processing. The accuracy and the robustness of tongue color and tongue coating color automatic analysis can be effectively enhanced by the method. The classification accuracy is high. Compared with the conventional "feature extraction + classifier" scheme, the convolutional neural network has an end-to-end structure, and the two processes of feature extraction and classification are completed under the same framework so that the dependence on feature and classifier selection can be avoided. The method has obvious advantages in the aspect of classification accuracy in comparison with the conventional method so as to meet the actual application requirements.

Description

technical field [0001] The present invention introduces deep learning technology into the objective research of TCM tongue diagnosis, and proposes an automatic analysis method of TCM tongue color and fur color based on convolutional neural network, which can effectively improve the accuracy and efficiency of automatic analysis of tongue color and fur color. Stickiness. The invention belongs to the field of computer vision and the field of tongue diagnosis of traditional Chinese medicine, and specifically relates to technologies such as deep learning and image processing. Background technique [0002] The automatic analysis of tongue features is an important part of the research on the objectivity of tongue diagnosis. Tongue color and fur color are the most basic characteristics of tongue image, so the automatic analysis of tongue color and fur color has become a research hotspot in the objectification of tongue diagnosis. The more commonly used automatic analysis methods o...

AI Technical Summary

Problems solved by technology

However, for the field of traditional Chinese medicine, high-quality data samples marked by authoritative doctors are not only scarce but also very expensive, while data marked by inexperienced doctors or non-professionals often lead to messy annotations, causing ambiguity, and the quality of data annotation is difficult. Guaranteed, this leads to a small library of labeled tongue images, and most existing CNN network structures cannot be directly used for automatic analysis of tongue color and fur color

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