Paper
24 November 2023 Tongue diagnosis method based on the percentage of the primary color of the tongue and H-component-assisted analysis
Yuchen Li, Xuefu Shang, Yuanyuan Xu, Yan Geng, Furui Tang, Gubin Cai, Fan Yang, Yawei Wang
Author Affiliations +
Proceedings Volume 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023); 129350A (2023) https://doi.org/10.1117/12.3000054
Event: Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 2023, Xi’an, China
Abstract
Tongue diagnosis is a way of aiding the diagnosis and identification of pathological conditions by observing tongue images in Chinese medicine diagnosis. The application of photo chromatography to diagnosis allows for the accurate and comprehensive extraction of tongue features. The main characteristic parameter of tongue diagnosis is color information, so this paper proposes a diagnostic method based on the proportion of the primary color of the tongue and the H-component to assist in the analysis. The method treats the tongue color and moss color as a whole, extracts the pixels and proportions of each tongue color and selects the primary color, uses a threshold method to distinguish between healthy and diseased tongue images based on the primary color proportion, and then uses a gray-scale histogram and H-component histogram to extract each feature parameter to achieve sub-classification of the diseased images. The experimental results show that the method is feasible, more stable and accurate than traditional methods, and can improve the diagnostic efficiency.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yuchen Li, Xuefu Shang, Yuanyuan Xu, Yan Geng, Furui Tang, Gubin Cai, Fan Yang, and Yawei Wang "Tongue diagnosis method based on the percentage of the primary color of the tongue and H-component-assisted analysis", Proc. SPIE 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 129350A (24 November 2023); https://doi.org/10.1117/12.3000054
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KEYWORDS
Tongue

Color

Histograms

RGB color model

Feature extraction

Image classification

Image processing

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