Laser & Optoelectronics Progress, Volume. 57, Issue 3, 031701(2020)

Tongue Diagnosis Method Based on Comparative Analysis of Tongue Image Chromatography

Wenwen Shang1, Yawei Wang2, Shuangshuang Xue2, Guangwei Peng2, Hao Han1, and Yuanyuan Xu2、*
Author Affiliations
  • 1School of Mechanical Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
  • 2Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013, China
  • show less

    Traditional tongue diagnosis information is mainly obtained by clinical subjective judgment, lacking objective and quantitative measures. Moreover, complexity of the patient self-state also affects accuracy of the diagnostic results. In this regard, a diagnostic method under the comparative analysis of self-tongue image chromatography is proposed. That is, use image processing techniques to overlay positive films of healthy tongue images and colored negative films of unhealthy tongue images, select the information sensitive area of the tongue images, collect the data, use the conversion relationship between RGB and CIE Lab color model, obtain the discrete chromatography distribution characteristics, and combine the quantitative parameter range to diagnose the health state. Through simulation and experimental analysis, the feasibility and correctness of the method are verified. The method proposed can effectively improve the tongue image diagnosis effect and is useful for the further development of tongue diagnosis in traditional Chinese medicine.

    Tools

    Get Citation

    Copy Citation Text

    Wenwen Shang, Yawei Wang, Shuangshuang Xue, Guangwei Peng, Hao Han, Yuanyuan Xu. Tongue Diagnosis Method Based on Comparative Analysis of Tongue Image Chromatography[J]. Laser & Optoelectronics Progress, 2020, 57(3): 031701

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Medical Optics and Biotechnology

    Received: Jun. 17, 2019

    Accepted: Aug. 5, 2019

    Published Online: Feb. 17, 2020

    The Author Email: Xu Yuanyuan (yuanyuanxulark@126.com)

    DOI:10.3788/LOP57.031701

    Topics