Image segmentation with context
(2007) 15th Scandinavian Image Analysis Conference 4522. p.283-292- Abstract
- We present a technique for simultaneous segmentation and classification of image partitions using combinatorial optimization techniques. By combining existing image segmentation approaches with simple learning techniques we show how prior knowledge can be incorporated into the visual grouping process through the formulation of a quadratic binary optimization problem. We further show how such to efficiently solve such problems through relaxation techniques and trust, region methods. This has resulted in an method that partitions images into a number of disjoint regions based on previously learned example segmentations. Preliminary experimental results are also presented in support of our suggested approach.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/643424
- author
- Eriksson, Anders P LU ; Olsson, Carl LU and Kahl, Fredrik LU
- organization
- publishing date
- 2007
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- visual grouping process, learning technique, combinatorial optimization technique, image segmentation, image classification, relaxation technique, quadratic binary optimization problem
- host publication
- Proceedings 15th Scandinavian Image Analysis Conference
- volume
- 4522
- pages
- 283 - 292
- publisher
- Springer
- conference name
- 15th Scandinavian Image Analysis Conference
- conference location
- Aalborg, Denmark
- conference dates
- 2007-06-10 - 2007-06-14
- external identifiers
-
- wos:000247364000029
- scopus:38049037993
- DOI
- 10.1007/978-3-540-73040-8_29
- language
- English
- LU publication?
- yes
- id
- c7e2ba1f-5614-42a5-9e49-c5b5ec9b1f0e (old id 643424)
- date added to LUP
- 2016-04-04 10:11:27
- date last changed
- 2022-01-29 19:53:46
@inproceedings{c7e2ba1f-5614-42a5-9e49-c5b5ec9b1f0e, abstract = {{We present a technique for simultaneous segmentation and classification of image partitions using combinatorial optimization techniques. By combining existing image segmentation approaches with simple learning techniques we show how prior knowledge can be incorporated into the visual grouping process through the formulation of a quadratic binary optimization problem. We further show how such to efficiently solve such problems through relaxation techniques and trust, region methods. This has resulted in an method that partitions images into a number of disjoint regions based on previously learned example segmentations. Preliminary experimental results are also presented in support of our suggested approach.}}, author = {{Eriksson, Anders P and Olsson, Carl and Kahl, Fredrik}}, booktitle = {{Proceedings 15th Scandinavian Image Analysis Conference}}, keywords = {{visual grouping process; learning technique; combinatorial optimization technique; image segmentation; image classification; relaxation technique; quadratic binary optimization problem}}, language = {{eng}}, pages = {{283--292}}, publisher = {{Springer}}, title = {{Image segmentation with context}}, url = {{http://dx.doi.org/10.1007/978-3-540-73040-8_29}}, doi = {{10.1007/978-3-540-73040-8_29}}, volume = {{4522}}, year = {{2007}}, }