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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73741
Title: 
Characterization of texture in image of skin lesions by support vector machine
Author(s): 
Institution: 
  • Universidade Estadual Paulista (UNESP)
  • Universidade Do Porto
ISSN: 
  • 2166-0727
  • 2166-0735
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.
Issue Date: 
19-Nov-2012
Citation: 
Iberian Conference on Information Systems and Technologies, CISTI. Information Systems and Technologies. New York: IEEE, p. 2, 2012.
Keywords: 
  • 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
Source: 
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6263217
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/73741
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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