Extraction of Tongue Region using Graph and Geometric Information

그래프 및 기하 정보를 이용한 설진 영역 추출

  • Published : 2007.11.01

Abstract

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

References

  1. C.-C. Chiu, 'A novel approach based on computerized image analysis for traditional Chinese medical diagnosis of the tongue', Computer Methods and Programs in Biomedicine, Vol. 61, pp. 77-89, 2000 https://doi.org/10.1016/S0169-2607(99)00031-0
  2. B.K. Lee, Oriental Medicine Diagnostics, Seoul, Korea: Seongbosa, pp. 72-86, 1996
  3. X.-Q. Yue and Q. Liu, 'Analysis of studies on pattern recognition of tongue image in traditional Chinese medicine by computer technology', J. Chin. Integr. Med., Vol. 2, No.5, pp. 326-329, 2004 https://doi.org/10.3736/jcim20040503
  4. B. Pang and D. Zhang, 'Computerized tongue diagnosis based on bayesian networks', IEEE Trans. Biomedical Engineering, Vol. 51, No. 10, pp. 1803-10, Oct. 2004 https://doi.org/10.1109/TBME.2004.831534
  5. H.Z. Zhang, K.Q. Wang, D. Zhang, B. Pang and B. Huang, 'Computer aided tongue diagnosis system', Proc. the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China, pp. 6754-6757, Sep. 2005
  6. L. Sun, Z. Cheng and H. Xie, 'Study on objective tongue diagnosis using computerized Image recognition technique', J. Anhui Traditional Chinese Medical College, Vol. 5, No.4, pp. 5-7, 1989
  7. J. Wu, Y. Zhang and J. Bai, 'Tongue area extraction in tongue diagnosis of traditional Chinese medicine', Proc. the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China, pp. 4955-4957, Sep. 2005
  8. B. Pang, K. Wang, D. Zhang and F. Zhang, 'On automated tongue image segmentation in Chinese medicine', ICPR, Vol. 1, pp. 616-619, 2002
  9. W. Li, C. Zhou and Z. Zhang, 'The segmentation of the body of tongue based on the improved snake algorithm in traditional Chinese medicine', Proc. the 5th world congress on intelligent control and automation, pp. 15-19, June 2004
  10. Y. Boykov and V. Kolmogorov, 'Computing geodesics and minimal surfaces via graph cuts', Proc. the 9th ICCV'03, pp. 26-33, Oct. 2003
  11. R. Zabih and V. Kolmogorov, 'Spatially coherent clustering using graph cuts', Proc. Computer Vision and Pattern Recognition, Vol. 2, pp. 437-444, July 2004
  12. C. Rother, V. Kolmogorov and A. Blake, 'GrabtCut: interactive foreground extraction using iterated graph cuts', ACM Trans. Graphics, Vol. 23, No.3, Aug. 2004
  13. V. Vezhnevets and V. Konouchine, 'Grow-Cut interactive multi-label N-D image segmentation', Proc. GraphiCon, pp. 150-156, 2005
  14. J.G. Kim, Development of Digital Tongue Inspection System, Suwon, Korea, Kyunghee Univ., Nov. 2005
  15. Y.H. Eo, Tongue segmentation and classification for Digital Tongue Inspection System, Master thesis, Seoul, Korea, Kyunghee Univ., Feb. 2006
  16. Color Conversion Formulas, http://www.easyrgb.com/math.html
  17. R.C. Gonzalez and R.E. Woods, Digital Image Processing, Reading, MA, USA: Addison Wesley, pp. 166-248, 1993
  18. I.M. Bockstein, 'Color equalization method and its application to color image processing', J, Opt. Soc. Amer., Vol. 3, No. 5, pp. 735 - 737, 1986 https://doi.org/10.1364/JOSAA.3.000735
  19. N. Liu and H. Yan, 'Colour image edge enhancement by two-channel process', Electronics Letters, Vol. 30, No. 12, p. 939-940, June 1994 https://doi.org/10.1049/el:19940642
  20. P.F. Felzenszwalb, 'Efficient graph-based image segmentation', International Journal of Computer Vision, Vol. 59, No.2, Sep. 2004
  21. J, Foley, A. van Dam, S. Feiner and J. Hughes, Computer Graphics: Principles and Practice (2nd edition), USA, Addison-Wesley, pp, 721-812, 1996