• DocumentCode
    2043108
  • Title

    Detection of skin lesions by fuzzy entropy based texel identification

  • Author

    Susan, Seba ; Hanmandlu, M. ; Madasu, Vamsi K. ; Lovell, Brian C.

  • Author_Institution
    I.I.T. Delhi, Delhi, India
  • fYear
    2009
  • fDate
    16-18 Sept. 2009
  • Firstpage
    244
  • Lastpage
    249
  • Abstract
    This paper proposes automated detection of skin lesions by unsupervised feature based clustering based on a new fuzzy entropy function for characterizing texture. The parameterized entropy function is optimized using the Bacterial Foraging algorithm. The clustering of the entropy function of the image is done using the popular Fuzzy C-means algorithm (FCM). The experimental results obtained after the clustering process indicate a very good segregation of texture clusters with satisfactory visual results. The results also provide us with the normalized entropy values needed for texel identification.
  • Keywords
    entropy; fuzzy logic; image texture; medical image processing; object detection; pattern clustering; automated skin lesion detection; bacterial foraging algorithm; entropy function clustering; fuzzy C-means algorithm; fuzzy entropy based texel identification; fuzzy entropy function; image texture characterisation; parameterised entropy function; texture cluster segregation; unsupervised feature based clustering; Clustering algorithms; Entropy; Fuzzy sets; Image processing; Image segmentation; Lesions; Microorganisms; Polynomials; Skin; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing and Analysis, 2009. ISPA 2009. Proceedings of 6th International Symposium on
  • Conference_Location
    Salzburg
  • ISSN
    1845-5921
  • Print_ISBN
    978-953-184-135-1
  • Type

    conf

  • DOI
    10.1109/ISPA.2009.5297716
  • Filename
    5297716