• DocumentCode
    1620884
  • Title

    Method of Reducing Dimensions of Segmentation Feature parameter Applied to Skin Erythema Image Segmentation

  • Author

    Shang, Keke ; Ying, Liu ; Hai-jing, Niu ; Yu-fu, Liu

  • Author_Institution
    Coll. of Sci., Tianjin Univ.
  • fYear
    2006
  • Firstpage
    3422
  • Lastpage
    3424
  • Abstract
    In this paper we discussed the method to reduce dimensions of segmentation feature applied to skin erythema image segmentation. Basing on analyzing a lot of erythema images, we proposed a new segmentation feature parameter applied to skin erythema image segmentation. At last, by using the fuzzy-c-means cluster arithmetic, we compared the segmentation speed and segmentation effect of adopting different segmentation features parameter and found that the segmentation result by using the new segmentation feature parameter is better
  • Keywords
    arithmetic; biomedical optical imaging; diseases; fuzzy set theory; image segmentation; medical image processing; skin; dimension reduction; fuzzy-c-means cluster arithmetic; image segmentation; segmentation feature parameter; skin erythema; Arithmetic; Diseases; Electromagnetic compatibility; Image analysis; Image color analysis; Image processing; Image segmentation; Laboratories; Pixel; Skin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1617213
  • Filename
    1617213