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Evidence-Based Complementary and Alternative Medicine
Volume 2015 (2015), Article ID 897580, 8 pages
http://dx.doi.org/10.1155/2015/897580
Research Article

Significant Geometry Features in Tongue Image Analysis

Department of Computer and Information Science, University of Macau, Taipa, Macau

Received 9 July 2014; Accepted 26 September 2014

Academic Editor: Guo-Zheng Li

Copyright © 2015 Bob Zhang and Han Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The shape of a human tongue and its relation to a patients’ state, either healthy or diseased (and if diseased which disease), is quantitatively analyzed using geometry features by means of computerized methods in this paper. Thirteen geometry features based on measurements, distances, areas, and their ratios are extracted from tongue images captured by a specially designed device with color correction. Using the features, 5 tongue shapes (rectangle, acute and obtuse triangles, square, and circle) are defined based on traditional Chinese medicine (TCM). Classification of the shapes is subsequently carried out with a decision tree. A large dataset consisting of 672 images comprising of 130 healthy and 542 disease examples (labeled according to Western medical practices) are tested. Experimental results show that the extracted geometry features are effective at tongue shape classification (coarse level). Even if more than one disease class belongs to the same shape, the disease classes can still be discriminated via fine level classification using a combination of the geometry features, with an average accuracy of 76.24% for all shapes.