Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
A scheme to develop the image over-segmentation task is introduced in this paper, it considers the pixels of an image as intuitive fuzzy sets and develops an intuitionistic clustering process of them. In this regard, the main contribution is to provide a method for extracting superpixels with greate...
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | México |
| Recursos: | UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO |
| Repositorio: | Journal of Applied Research and Technology |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs2.localhost:article/1581 |
| Acesso em linha: | https://jart.icat.unam.mx/index.php/jart/article/view/1581 |
| Access Level: | acceso abierto |
| Palavra-chave: | superpixels extraction intuitionistic fuzzy clustering biomedical grayscale and natural color images |
| Resumo: | A scheme to develop the image over-segmentation task is introduced in this paper, it considers the pixels of an image as intuitive fuzzy sets and develops an intuitionistic clustering process of them. In this regard, the main contribution is to provide a method for extracting superpixels with greater adherence to the edges of the regions. Experimental tests were developed considering biomedical grayscale and natural color images. The robustness and effectiveness of this proposal was verified by quantitative and qualitative results. |
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