Abstract
We propose a deformable model for manually initialized segmentation of images, which may contain both textured and non-textured regions. Image segments and segment boundaries are represented using a deformable triangle mesh, providing all advantages of an explicit geometry representation, but allowing for adaptive topology. Deformation forces are computed using a probabilistic model of local self-similarity, based on clustering of image patches. Both our curve representation and our similarity model naturally support multi-label segmentation. We demonstrate the properties of our approach on a number of natural color images as well as composed textured images.
Original language | English |
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Title of host publication | Proceedings of 2019 IEEE International Conference on Image Processing |
Publisher | IEEE |
Publication date | 2019 |
Pages | 2731-2735 |
ISBN (Print) | 978-1-5386-6249-6 |
DOIs | |
Publication status | Published - 2019 |
Event | 2019 IEEE International Conference on Image Processing - Taipei International Convention Center, Taipei, Taiwan, Province of China Duration: 22 Sept 2019 → 25 Sept 2019 https://www.2019.ieeeicip.org/2019.ieeeicip.org/index-2.html |
Conference
Conference | 2019 IEEE International Conference on Image Processing |
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Location | Taipei International Convention Center |
Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 22/09/2019 → 25/09/2019 |
Internet address |
Keywords
- Textured segmentation
- Adaptive triangle mesh
- Mumford-Shah