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- Publisher Website: 10.1109/TIP.2012.2187670
- Scopus: eid_2-s2.0-84861168124
- PMID: 22345535
- WOS: WOS:000304159800004
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Article: A semisupervised segmentation model for collections of images
Title | A semisupervised segmentation model for collections of images |
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Authors | |
Keywords | Biological image segmentation Multiple images Microscopy images Interactive Image segmentation |
Issue Date | 2012 |
Citation | IEEE Transactions on Image Processing, 2012, v. 21, n. 6, p. 2955-2968 How to Cite? |
Abstract | In this paper, we consider the problem of segmentation of large collections of images. We propose a semisupervised optimization model that determines an efficient segmentation of many input images. The advantages of the model are twofold. First, the segmentation is highly controllable by the user so that the user can easily specify what he/she wants. This is done by allowing the user to provide, either offline or interactively, some (fully or partially) labeled pixels in images as strong priors for the model. Second, the model requires only minimal tuning of model parameters during the initial stage. Once initial tuning is done, the setup can be used to automatically segment a large collection of images that are distinct but share similar features. We will show the mathematical properties of the model such as existence and uniqueness of solution and establish a maximum/minimum principle for the solution of the model. Extensive experiments on various collections of biological images suggest that the proposed model is effective for segmentation and is computationally efficient. © 2012 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/276918 |
ISSN | 2023 Impact Factor: 10.8 2023 SCImago Journal Rankings: 3.556 |
ISI Accession Number ID |
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 | 2019-09-18T08:35:03Z | - |
dc.date.available | 2019-09-18T08:35:03Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | IEEE Transactions on Image Processing, 2012, v. 21, n. 6, p. 2955-2968 | - |
dc.identifier.issn | 1057-7149 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276918 | - |
dc.description.abstract | In this paper, we consider the problem of segmentation of large collections of images. We propose a semisupervised optimization model that determines an efficient segmentation of many input images. The advantages of the model are twofold. First, the segmentation is highly controllable by the user so that the user can easily specify what he/she wants. This is done by allowing the user to provide, either offline or interactively, some (fully or partially) labeled pixels in images as strong priors for the model. Second, the model requires only minimal tuning of model parameters during the initial stage. Once initial tuning is done, the setup can be used to automatically segment a large collection of images that are distinct but share similar features. We will show the mathematical properties of the model such as existence and uniqueness of solution and establish a maximum/minimum principle for the solution of the model. Extensive experiments on various collections of biological images suggest that the proposed model is effective for segmentation and is computationally efficient. © 2012 IEEE. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Image Processing | - |
dc.subject | Biological image segmentation | - |
dc.subject | Multiple images | - |
dc.subject | Microscopy images | - |
dc.subject | Interactive | - |
dc.subject | Image segmentation | - |
dc.title | A semisupervised segmentation model for collections of images | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TIP.2012.2187670 | - |
dc.identifier.pmid | 22345535 | - |
dc.identifier.scopus | eid_2-s2.0-84861168124 | - |
dc.identifier.volume | 21 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 2955 | - |
dc.identifier.epage | 2968 | - |
dc.identifier.isi | WOS:000304159800004 | - |
dc.identifier.issnl | 1057-7149 | - |