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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.09137 |
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| _version_ | 1866910697417342976 |
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| author | Gilles, Jérôme Collin, Bertrand |
| author_facet | Gilles, Jérôme Collin, Bertrand |
| contents | Few people use the probability theory in order to achieve image segmentation with snake models. In this article, we are presenting an active contour algorithm based on a probability approach inspired by A. Blake work and P. R{é}fr{é}gier's team research in France. Our algorithm, both very fast and highly accurate as far as contour description is concerned, is easily adaptable to any specific application. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_09137 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fast probabilistic snake algorithm Gilles, Jérôme Collin, Bertrand Image and Video Processing Computer Vision and Pattern Recognition Few people use the probability theory in order to achieve image segmentation with snake models. In this article, we are presenting an active contour algorithm based on a probability approach inspired by A. Blake work and P. R{é}fr{é}gier's team research in France. Our algorithm, both very fast and highly accurate as far as contour description is concerned, is easily adaptable to any specific application. |
| title | Fast probabilistic snake algorithm |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2411.09137 |