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Conference Paper: Interactive segmentation of multiple images
Title | Interactive segmentation of multiple images |
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Authors | |
Keywords | Interactive Bioimage segmentation Multiple images Microscopy images Image segmentation |
Issue Date | 2011 |
Citation | Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011, 2011, v. 2, p. 571-575 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/276482 |
DC Field | Value | Language |
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dc.contributor.author | Law, Yan Nei | - |
dc.contributor.author | Lee, Hwee Kuan | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Yip, Andy M. | - |
dc.date.accessioned | 2019-09-18T08:33:44Z | - |
dc.date.available | 2019-09-18T08:33:44Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011, 2011, v. 2, p. 571-575 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276482 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 | - |
dc.subject | Interactive | - |
dc.subject | Bioimage segmentation | - |
dc.subject | Multiple images | - |
dc.subject | Microscopy images | - |
dc.subject | Image segmentation | - |
dc.title | Interactive segmentation of multiple images | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.scopus | eid_2-s2.0-84864942656 | - |
dc.identifier.volume | 2 | - |
dc.identifier.spage | 571 | - |
dc.identifier.epage | 575 | - |