Title :
Differential Evolution Algorithm For Segmentation Of Wound Images
Author :
Aslantas, Veysel ; Tunckanat, Mehmet
Author_Institution :
Erciyes Univ., Kayseri
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;
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
DOI :
10.1109/WISP.2007.4447606