Differential Evolution Algorithm For Segmentation Of Wound Images

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 op...

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Bibliographic Details
Published in2007 IEEE International Workshop on Intelligent Signal Processing pp. 1 - 5
Main Authors Aslantas, V., Tunckanat, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2007
Subjects
Arithmetic
Clustering algorithms
diferential evolution
Genetic mutations
Image converters
Image segmentation
Lesions
Skin
Statistics
Surface fitting
wound
Wounds
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ISBN9781424408290
1424408296
DOI10.1109/WISP.2007.4447606

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Summary: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.
ISBN:9781424408290
1424408296
DOI:10.1109/WISP.2007.4447606