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http://acervodigital.unesp.br/handle/11449/73741
- Title:
- Characterization of texture in image of skin lesions by support vector machine
- Universidade Estadual Paulista (UNESP)
- Universidade Do Porto
- 2166-0727
- 2166-0735
- 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.
- 19-Nov-2012
- Iberian Conference on Information Systems and Technologies, CISTI. Information Systems and Technologies. New York: IEEE, p. 2, 2012.
- 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
- http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6263217
- Acesso restrito
- outro
- http://repositorio.unesp.br/handle/11449/73741
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