NDLI: A Linear Framework for Region-Based Image Segmentation and Inpainting Involving Curvature Penalization

Content Provider	Springer Nature Link
Author	Schoenemann, Thomas Kahl, Fredrik Masu, Simon Cremers, Daniel
Copyright Year	2012
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.
Starting Page	53
Ending Page	68
Page Count	16
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	99
Issue Number	1
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2012-03-03
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Curvature regularity Image segmentation Inpainting Linear programming Cell complexes Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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