A Linear Framework for Region-Based Image Segmentation and Inpainting Involving Curvature Penalization
(2012) In International Journal of Computer Vision 99(1). p.53-68- Abstract
- We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start from a new formulation of length-based optimization schemes, based on surface continuation constraints, and discuss the connections to existing schemes. The formulation is based on a cell complex and considers basic regions and boundary elements. The corresponding optimization problem is cast as an integer linear program. We then show how the method can be extended to include curvature regularity, again cast as an integer linear program. Here, we are considering pairs of boundary elements to reflect curvature. Moreover, a constraint set is derived to ensure that the... (More)
- We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start from a new formulation of length-based optimization schemes, based on surface continuation constraints, and discuss the connections to existing schemes. The formulation is based on a cell complex and considers basic regions and boundary elements. The corresponding optimization problem is cast as an integer linear program. We then show how the method can be extended to include curvature regularity, again cast as an integer linear program. Here, we are considering pairs of boundary elements to reflect curvature. Moreover, a constraint set is derived to ensure that the boundary variables indeed reflect the boundary of the regions described by the region variables. We show that by solving the linear programming relaxation one gets reasonably close to the global optimum, and that curvature regularity is indeed much better suited in the presence of long and thin objects compared to standard length regularity. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2545372
- author
- Schoenemann, Thomas LU ; Kahl, Fredrik LU ; Masnou, Simon and Cremers, Daniel
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Curvature regularity, Image segmentation, Inpainting, Linear, programming, Cell complexes
- in
- International Journal of Computer Vision
- volume
- 99
- issue
- 1
- pages
- 53 - 68
- publisher
- Springer
- external identifiers
-
- wos:000303525200003
- scopus:84860525582
- ISSN
- 1573-1405
- DOI
- 10.1007/s11263-012-0518-7
- language
- English
- LU publication?
- yes
- id
- 6813f155-fe53-4684-b683-c8f96686b699 (old id 2545372)
- date added to LUP
- 2016-04-01 11:10:11
- date last changed
- 2022-04-28 07:49:42
@article{6813f155-fe53-4684-b683-c8f96686b699,
abstract = {{We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start from a new formulation of length-based optimization schemes, based on surface continuation constraints, and discuss the connections to existing schemes. The formulation is based on a cell complex and considers basic regions and boundary elements. The corresponding optimization problem is cast as an integer linear program. We then show how the method can be extended to include curvature regularity, again cast as an integer linear program. Here, we are considering pairs of boundary elements to reflect curvature. Moreover, a constraint set is derived to ensure that the boundary variables indeed reflect the boundary of the regions described by the region variables. We show that by solving the linear programming relaxation one gets reasonably close to the global optimum, and that curvature regularity is indeed much better suited in the presence of long and thin objects compared to standard length regularity.}},
author = {{Schoenemann, Thomas and Kahl, Fredrik and Masnou, Simon and Cremers, Daniel}},
issn = {{1573-1405}},
keywords = {{Curvature regularity; Image segmentation; Inpainting; Linear; programming; Cell complexes}},
language = {{eng}},
number = {{1}},
pages = {{53--68}},
publisher = {{Springer}},
series = {{International Journal of Computer Vision}},
title = {{A Linear Framework for Region-Based Image Segmentation and Inpainting Involving Curvature Penalization}},
url = {{http://dx.doi.org/10.1007/s11263-012-0518-7}},
doi = {{10.1007/s11263-012-0518-7}},
volume = {{99}},
year = {{2012}},
}