Effective Features to Classify Skin Lesions in Dermoscopic images
Features such as shape and color are indispensable to determine whether a skin lesion is a melanoma or not. However, there are no fixed guidelines to define which features are effective and how to combine them for classification. This lack of definition impedes the development of the automatic analy...
| Autor principal: | |
|---|---|
| Outros Autores: | |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2017
|
| Assuntos: | |
| Texto completo: | https://hdl.handle.net/10216/104033 |
| País: | Portugal |
| Oai: | oai:repositorio-aberto.up.pt:10216/104033 |
| Resumo: | Features such as shape and color are indispensable to determine whether a skin lesion is a melanoma or not. However, there are no fixed guidelines to define which features are effective and how to combine them for classification. This lack of definition impedes the development of the automatic analyses of dermoscopic images. In this work, a search for effective features was carried out using a support vector machine. Three image databases were used to verify the feasibility and sensitivity of the automatic classification used. The results showed which features had a major influence on the classification performance, and confirmed the need to use various types of features in this process. |
|---|