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Texture aware image segmentation using graph cuts and active contours

Zhou, Hailing, Zheng, J and Wei, Lei 2013, Texture aware image segmentation using graph cuts and active contours, Pattern recognition, vol. 46, no. 6, pp. 1719-1733, doi: 10.1016/j.patcog.2012.12.005.

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Title Texture aware image segmentation using graph cuts and active contours
Author(s) Zhou, HailingORCID iD for Zhou, Hailing orcid.org/0000-0001-5009-4330
Zheng, J
Wei, LeiORCID iD for Wei, Lei orcid.org/0000-0001-8267-0283
Journal name Pattern recognition
Volume number 46
Issue number 6
Start page 1719
End page 1733
Total pages 15
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2013-06
ISSN 0031-3203
1873-5142
Keyword(s) interactive image segmentation
graph cut
active contour
color-texture
structure tensor
Science & Technology
Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Computer Science
Engineering
MINIMIZATION
FRAMEWORK
GRABCUT
MODEL
Summary The problem of segmenting a foreground object out from its complex background is of great interest in image processing and computer vision. Many interactive segmentation algorithms such as graph cut have been successfully developed. In this paper, we present four technical components to improve graph cut based algorithms, which are combining both color and texture information for graph cut, including structure tensors in the graph cut model, incorporating active contours into the segmentation process, and using a “softbrush” tool to impose soft constraints to refine problematic boundaries. The integration of these components provides an interactive segmentation method that overcomes the difficulties of previous segmentation algorithms in handling images containing textures or low contrast boundaries and producing a smooth and accurate segmentation boundary. Experiments on various images from the Brodatz, Berkeley and MSRC data sets are conducted and the experimental results demonstrate the high effectiveness of the proposed method to a wide range of images
Language eng
DOI 10.1016/j.patcog.2012.12.005
Field of Research 080109 Pattern Recognition and Data Mining
080106 Image Processing
0899 Other Information And Computing Sciences
0906 Electrical And Electronic Engineering
0801 Artificial Intelligence And Image Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050994

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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Created: Tue, 05 Mar 2013, 15:18:06 EST

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