A study of lesion skin segmentation, features selection and classification approaches
| Autor: | Youssef Filali, Assia Ennouni, My Abdelouahed Sabri, Abdellah Aarab |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry Feature extraction 020207 software engineering Pattern recognition 02 engineering and technology Image segmentation medicine.disease Statistical classification Feature (computer vision) Component (UML) 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Segmentation Artificial intelligence Skin cancer business Selection (genetic algorithm) |
| Zdroj: | 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). |
| DOI: | 10.1109/isacv.2018.8354069 |
| Popis: | Among the most dangerous cancer in the world is skin cancer. If not diagnosed in early stages it might be hard to cure. The aim of this work is to present a study of skin segmentation, features selection and classification approaches. In the segmentation stage, we will present the result of the use of a pre-processing based on a multiscale decomposition model where geometrical component is used to get a good segmentation. The features are firstly extracted using the texture component and color of the lesion, and then we will present a comparative study of some features selection approaches that select the relevant ones. In feature classification we will compare between the most and good classifiers used in literature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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