dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | Universidade Do Porto | |
dc.date.accessioned | 2014-05-27T11:27:09Z | |
dc.date.available | 2014-05-27T11:27:09Z | |
dc.date.created | 2014-05-27T11:27:09Z | |
dc.date.issued | 2012-11-19 | |
dc.identifier | Iberian Conference on Information Systems and Technologies, CISTI. Information Systems and Technologies. New York: IEEE, p. 2, 2012. | |
dc.identifier | 2166-0727 | |
dc.identifier | 2166-0735 | |
dc.identifier | http://hdl.handle.net/11449/73741 | |
dc.identifier | WOS:000319285900159 | |
dc.identifier | 2-s2.0-84869038704 | |
dc.identifier | 6542086226808067 | |
dc.identifier | 0000-0002-0924-8024 | |
dc.description.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. | |
dc.language | por | |
dc.relation | Iberian Conference on Information Systems and Technologies, CISTI | |
dc.relation | 0,136 | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | box-counting method | |
dc.subject | fractal dimension | |
dc.subject | intelligent system | |
dc.subject | machine learning | |
dc.subject | support vector machine | |
dc.subject | Box-counting method | |
dc.subject | Feature vectors | |
dc.subject | Skin cancers | |
dc.subject | Skin lesion | |
dc.subject | Dermatology | |
dc.subject | Fractal dimension | |
dc.subject | Image retrieval | |
dc.subject | Information systems | |
dc.subject | Intelligent systems | |
dc.subject | Learning systems | |
dc.subject | Support vector machines | |
dc.subject | Textures | |
dc.subject | Image texture | |
dc.title | Characterization of texture in image of skin lesions by support vector machine | |
dc.type | Actas de congresos | |