article

Texture aware image segmentation using graph cuts and active contours

Authors:

Lei WeiAuthors Info & Claims

Pattern Recognition, Volume 46, Issue 6

Pages 1719 - 1733

https://doi.org/10.1016/j.patcog.2012.12.005

Published: 01 June 2013 Publication History

Abstract

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.

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Cited By

Malik JKiranyaz SAl-Raoush RMonga OGarnier PFoufou SBouras AIosifidis AGabbouj MBaveye P(2022)3D Quantum Cuts for automatic segmentation of porous media in tomography imagesComputers & Geosciences10.1016/j.cageo.2021.105017159:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.cageo.2021.105017
Wang ZGao XWu RKang JZhang Y(2022)Fully automatic image segmentation based on FCN and graph cutsMultimedia Systems10.1007/s00530-022-00945-328:5(1753-1765)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s00530-022-00945-3
Wang TYang JJi ZSun Q(2019)Probabilistic Diffusion for Interactive Image SegmentationIEEE Transactions on Image Processing10.1109/TIP.2018.286794128:1(330-342)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TIP.2018.2867941
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Texture aware image segmentation using graph cuts and active contours
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems

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Published In

cover image Pattern Recognition

Pattern Recognition Volume 46, Issue 6

June, 2013

225 pages

ISSN:0031-3203

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Copyright © Elsevier Ltd © 2012.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 June 2013

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Cited By

Malik JKiranyaz SAl-Raoush RMonga OGarnier PFoufou SBouras AIosifidis AGabbouj MBaveye P(2022)3D Quantum Cuts for automatic segmentation of porous media in tomography imagesComputers & Geosciences10.1016/j.cageo.2021.105017159:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.cageo.2021.105017
Wang ZGao XWu RKang JZhang Y(2022)Fully automatic image segmentation based on FCN and graph cutsMultimedia Systems10.1007/s00530-022-00945-328:5(1753-1765)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s00530-022-00945-3
Wang TYang JJi ZSun Q(2019)Probabilistic Diffusion for Interactive Image SegmentationIEEE Transactions on Image Processing10.1109/TIP.2018.286794128:1(330-342)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TIP.2018.2867941
Rahbar K(2019)Image segmentation through modeling the illumination probability distribution function using the Krawtchouk polynomialSignal Processing10.1016/j.sigpro.2019.05.033164:C(1-9)Online publication date: 1-Nov-2019
https://dl.acm.org/doi/10.1016/j.sigpro.2019.05.033
Subudhi PMukhopadhyay S(2019)An efficient graph reduction framework for interactive texture segmentationImage Communication10.1016/j.image.2019.01.01074:C(42-53)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1016/j.image.2019.01.010
Breve F(2019)Interactive image segmentation using label propagation through complex networksExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.01.031123:C(18-33)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1016/j.eswa.2019.01.031
Feng LLi HGao YZhang Y(2019)A Color Image Segmentation Method Based on Region Salient Color and Fuzzy C-Means AlgorithmCircuits, Systems, and Signal Processing10.1007/s00034-019-01126-w39:2(586-610)Online publication date: 30-Apr-2019
https://dl.acm.org/doi/10.1007/s00034-019-01126-w
Beheshti MAshapure ARahnemoonfar MFaichney J(2018)Fluorescence microscopy image segmentation based on graph and fuzzy methodsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-1746634:4(2563-2578)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.3233/JIFS-17466
Zhang ZXing FWang HYan YHuang YShi XYang L(2018)Revisiting graph construction for fast image segmentationPattern Recognition10.1016/j.patcog.2018.01.03778:C(344-357)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1016/j.patcog.2018.01.037
Wang TYang JSun QJi ZFu PGe Q(2018)Global graph diffusion for interactive object extractionInformation Sciences: an International Journal10.1016/j.ins.2018.05.040460:C(103-114)Online publication date: 1-Sep-2018
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