On selection of centroids of fuzzy clusters for color classification
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866909266975129600 |
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| author | Kim, Dae-Won Lee, Kwang H. |
| author_facet | Kim, Dae-Won Lee, Kwang H. |
| contents | A novel initialization method in the fuzzy c-means (FCM) algorithm is proposed for the color clustering problem. Given a set of color points, the proposed initialization extracts dominant colors that are the most vivid and distinguishable colors. Color points closest to the dominant colors are selected as initial centroids in the FCM. To obtain the dominant colors and their closest color points, we introduce reference colors and define a fuzzy membership model between a color point and a reference color. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_17423 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On selection of centroids of fuzzy clusters for color classification Kim, Dae-Won Lee, Kwang H. Computer Vision and Pattern Recognition A novel initialization method in the fuzzy c-means (FCM) algorithm is proposed for the color clustering problem. Given a set of color points, the proposed initialization extracts dominant colors that are the most vivid and distinguishable colors. Color points closest to the dominant colors are selected as initial centroids in the FCM. To obtain the dominant colors and their closest color points, we introduce reference colors and define a fuzzy membership model between a color point and a reference color. |
| title | On selection of centroids of fuzzy clusters for color classification |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2407.17423 |