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Characterization of texture in image of skin lesions by support vector machine

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Abstract

Due to the increased incidence of skin cancer, computational methods based on intelligent approaches have been developed to aid dermatologists in the diagnosis of skin lesions. This paper proposes a method to classify texture in images, since it is an important feature for the successfully identification of skin lesions. For this is defined a feature vector, with the fractal dimension of images through the box-counting method (BCM), which is used with a SVM to classify the texture of the lesions in to non-irregular or irregular. With the proposed solution, we could obtain an accuracy of 72.84%. © 2012 AISTI.

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box-counting method, fractal dimension, intelligent system, machine learning, support vector machine, Box-counting method, Feature vectors, Skin cancers, Skin lesion, Dermatology, Fractal dimension, Image retrieval, Information systems, Intelligent systems, Learning systems, Support vector machines, Textures, Image texture

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Portuguese

Citation

Iberian Conference on Information Systems and Technologies, CISTI. Information Systems and Technologies. New York: IEEE, p. 2, 2012.

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