Abstract
In this paper, we propose an optimization model for interactive segmentation of multiple images. The user marks some sample pixels or objects in one or more images. Then, the method employs the samples as strong priors to automatically segment other input images. A good feature of the method is that the segmentation is highly controllable by the user, so that the user can easily obtain the kind of objects that he/she wants. The approach is especially effective for segmentation of a large collection of images that share similar features, where the user inputs some samples once and for all. We demonstrate the usefulness of the model to the segmentation of various collections of bioimages.
| Original language | English |
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| Title of host publication | Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 |
| Pages | 571-575 |
| Number of pages | 5 |
| Publication status | Published - 2011 |
| Event | 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 - Las Vegas, NV, United States Duration: 18 Jul 2011 → 21 Jul 2011 |
Publication series
| Name | Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 |
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| Volume | 2 |
Conference
| Conference | 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 |
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| Country/Territory | United States |
| City | Las Vegas, NV |
| Period | 18/07/11 → 21/07/11 |
User-Defined Keywords
- Bioimage segmentation
- Image segmentation
- Interactive
- Microscopy images
- Multiple images