• 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