• DocumentCode
    2953034
  • Title

    Differential Evolution Algorithm For Segmentation Of Wound Images

  • Author

    Aslantas, Veysel ; Tunckanat, Mehmet

  • Author_Institution
    Erciyes Univ., Kayseri
  • fYear
    2007
  • fDate
    3-5 Oct. 2007
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Color-based region segmentation of skin lesions is one of the key steps for correctly collecting statistics that can help clinicians in their diagnosis. This study describes the use of differential evolution algorithm for segmentation of wounds on the skin. The abilities of differential evolution optimization algorithm, such as easiness, simple operations using, effectiveness and converging to global optimum reflected to wound image segmentation by using differential evolution algorithm in image segmentation. The system does not have the disadvantages of classical systems such as K-means clustering algorithm and the results obtained from different wound images have been discussed.
  • Keywords
    evolutionary computation; image colour analysis; image segmentation; medical image processing; optimisation; pattern clustering; skin; DE clustering algorithm; clinical diagnosis; color-based region segmentation; differential evolution optimization algorithm; skin lesions; wound image segmentation; Arithmetic; Clustering algorithms; Genetic mutations; Image converters; Image segmentation; Lesions; Skin; Statistics; Surface fitting; Wounds; diferential evolution; image segmentation; wound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on
  • Conference_Location
    Alcala de Henares
  • Print_ISBN
    978-1-4244-0830-6
  • Electronic_ISBN
    978-1-4244-0830-6
  • Type

    conf

  • DOI
    10.1109/WISP.2007.4447606
  • Filename
    4447606