DocumentCode :
2337361
Title :
Comparing nonlinear derivative method and Canny algorithm to tongue diagnosis in Traditional Chinese Medicine
Author :
Chen, Yen-Sheng ; Chang, Yuh-Ming ; Chen, Chung-Hua
Author_Institution :
Dept. of Creative Product & Technol. Applic., Lan Yang Inst. of Technol., Toucheng, Taiwan
fYear :
2012
fDate :
3-5 June 2012
Firstpage :
407
Lastpage :
409
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. 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 Canny and nonlinear derivative methods for edge segmentation. The segmentation using Canny algorithm may produce many false edges after cutting; thus, it is not suitable for use. But, nonlinear derivative 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.
Keywords :
edge detection; image segmentation; medicine; patient diagnosis; Canny algorithm; automated tongue diagnosis system; automatic tongue diagnostic system; edge detection; edge segmentation; false edge; human tongue; nonlinear derivative method; traditional chinese medicine; Filter banks; Image edge detection; Image segmentation; Medical diagnostic imaging; Noise; Tongue; canny algorithm; image edge detection; nonlinear derivative method; tongue diagnosis; traditional Chinese medicine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
Type :
conf
DOI :
10.1109/ISRA.2012.6219210
Filename :
6219210
Link To Document :
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