Comparing Intuitionistic Fuzzy Set Theory Method and Canny Algorithm for Edge Detection to Tongue Diagnosis in Traditional Chinese Medicine
- DOI
- 10.2991/iccia.2012.353How to use a DOI?
- Keywords
- tongue diagnosis, traditional chinese medicine, intuitionistic fuzzy set theory, canny algorithm, image edge detection
- Abstract
The tongue diagnosis is an important diagnostic method in Traditional Chinese Medicine (TCM). Human tongue is one of the im¬portant 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 me¬thod 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.
- Copyright
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yensheng Chen AU - Yuhming Chang AU - Jiunncherng Lin PY - 2014/05 DA - 2014/05 TI - Comparing Intuitionistic Fuzzy Set Theory Method and Canny Algorithm for Edge Detection to Tongue Diagnosis in Traditional Chinese Medicine BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 1424 EP - 1427 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.353 DO - 10.2991/iccia.2012.353 ID - Chen2014/05 ER -