NDLI: Image segmentation with pseudo branch and bound algorithm

Content Provider	IEEE Xplore Digital Library
Author	Hong-Gui Li Xing-Guo Li
Copyright Year	2009
Description	Author affiliation: Department of Electronic Engineering, Nanjing University of Science and Technology, 210094, China (Xing-Guo Li) \|\| Physics College, Yang zhou University, 225002, China (Hong-Gui Li)
Abstract	Improved branch and minicut method for image segmentation is proposed. The most valuable contribution of proposed algorithm is that, accelerating branch and minicut method, avoiding exhaustive search on whole parameter space, and preserving segmentation quality at the same time, by loosening the condition of being a leaf node. Branch and minicut method utilizes branch and bound algorithm to explore the global minimum of energy function, and the lower bounds of branch and bound algorithm is quickly evaluated by graph cuts algorithm. Pseudo branch and bound algorithm is proposed, through relaxing the update condition of current optimal solution, which is equal to loosening the condition of being a leaf node in branch and minicut method. Experiments results of gray scale and color image segmentation show, proposed algorithm is faster than branch and minicut method, and has almost the same segmentation ability.
Starting Page	2448
Ending Page	2452
File Size	690364
Page Count	5
File Format	PDF
ISBN	9781424437023
DOI	10.1109/ICMLC.2009.5212215
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Machine learning Cybernetics graph cuts Branch and bound image segmentation branch and minicut grabcut
Content Type	Text
Resource Type	Article

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