Sub-Markov random walk for image segmentation

Dong, Xingping, Shen, Jianbing, Shao, Ling and Van Gool, Luc (2016) Sub-Markov random walk for image segmentation. IEEE Transactions on Image Processing, 25 (2). pp. 516-527. ISSN 1057-7149

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Abstract

A novel sub-Markov random walk (subRW) algorithm with label prior is proposed for seeded image segmentation, which can be interpreted as a traditional random walker on a graph with added auxiliary nodes. Under this explanation, we unify the proposed subRW and other popular random walk (RW) algorithms. This unifying view will make it possible for transferring intrinsic findings between different RW algorithms, and offer new ideas for designing novel RW algorithms by adding or changing auxiliary nodes. To verify the second benefit, we design a new subRW algorithm with label prior to solve the segmentation problem of objects with thin and elongated parts. The experimental results on both synthetic and natural images with twigs demonstrate that the proposed subRW method outperforms previous RW algorithms for seeded image segmentation.

Item Type:	Article
Additional Information:	(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Faculty \ School:	Faculty of Science > School of Computing Sciences
Depositing User:	Pure Connector
Date Deposited:	16 Feb 2017 02:20
Last Modified:	21 Oct 2022 08:33
URI:	https://ueaeprints.uea.ac.uk/id/eprint/62616
DOI:	10.1109/TIP.2015.2505184

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