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Proceedings Paper

Tongue's substance and coating recognition analysis using HSV color threshold in tongue diagnosis
Author(s): Nur Diyana Kamarudin; Chia Yee Ooi; Tadaaki Kawanabe; Xiaoyu Mi
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Paper Abstract

In ISO TC249 conference, tongue diagnosis has been one of the most active research and their objectifications has become significant with the help of numerous statistical and machine learning algorithm. Color information of substance or tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. In order to produce high reproducibility of color measurement analysis, tongue images have to undergo several procedures such as color correction, segmentation and tongue’s substance-coating separation. This paper presents a novel method to recognize substance and coating from tongue images and eliminate the tongue coating for accurate substance color measurement for diagnosis. By utilizing Hue, Saturation, Value (HSV) color space, new color-brightness threshold parameters have been devised to improve the efficiency of tongue’s substance and coating separation procedures and eliminate shadows. The algorithm offers fast processing time around 0.98 seconds for 60,000 pixels tongue image. The successful tongue’s substance and coating separation rate reported is 90% compared to the labelled data verified by the practitioners. Using 300 tongue images, the substance Lab color measurement with small standard deviation had revealed the effectiveness of this proposed method in computerized tongue diagnosis system.

Paper Details

Date Published: 11 July 2016
PDF: 5 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100110J (11 July 2016); doi: 10.1117/12.2242404
Show Author Affiliations
Nur Diyana Kamarudin, Malaysia-Japan International Institute of Technology (Malaysia)
Chia Yee Ooi, Malaysia-Japan International Institute of Technology (Malaysia)
Tadaaki Kawanabe, Kitasato Univ. (Japan)
Xiaoyu Mi, Fujitsu Labs. Ltd. (Japan)

Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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