Comparing Intuitionistic Fuzzy Set Theory Method and Canny Algorithm for Edge Detection to Tongue Diagnosis in Traditional Chinese Medicine

Abstract:

The tongue diagnosis is an important diagnostic method in Traditional Chinese Medicine (TCM). Human tongue is one of the im­portant organs which contain the information of health status. Image segmentation has always been a fundamental problem and complex task in the field of image processing and computer vision. Its goal is to change the representation of an image into something that is more meaningful and easier to analyze. In other words, it is used to partition a given image into several parts in each of which the intensity is homogeneous. In order to achieve an automatic tongue diagnostic system, an effective segmentation me­thod for detecting the edge of tongue is very important. We mainly compare the Chan Vese Method and Canny algorithm for edge segmentation. The segmentation using Canny algorithm may produce many false edges after cutting; thus, it is not suitable for use. But, for our two steps Chan Vese method can automatically select the best edge information. Therefore, it may be useful in clinical automated tongue diagnosis system. Experiments show the results of these techniques.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 3771-3774
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.3771
• Online since: September 2013
• Authors: Yen Sheng Chen, Yuh Ming Chang, Jiunn Cherng Lin
• Keywords: Canny Algorithm, Image Edge Detection, Intuitionistic Fuzzy Set Theory, Tongue Diagnosis, Traditional Chinese Medicine

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