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A Novel Graph Cut Algorithm for Weak Boundary Object Segmentation

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Foundations of Intelligent Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 277))

Abstract

Image segmentation plays an important role in high-level visual recognition tasks. In recent years, the combinatorial graph cut algorithm has been successfully applied to image segmentation because it offers numerically robust global minimum. For low-level image segmentation, intensity is a widely used regional cue. However, when comes to weak boundary, it is often not enough to discriminate the object of interest. In this paper, we extend the standard graph cut algorithm by taking into account the gradient direction of neighboring pixels as an additional cue. A new energy function is proposed to fuse the intensity and gradient cues. Experimental results show that our method is more robust and helpful to detect the low-contrast boundaries.

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Acknowledgments

This work is supported by the National Science Foundation of China under Grants 61202190 and 61175047, the Science and Technology Planning Project of Sichuan Province under Grant 2012RZ0008, and by the Fundamental Research Funds for the Central Universities under Grant 2682013CX055.

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Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 610031, China

    Hongmei Tian, Bo Peng & Tianrui Li

  2. Sichuan Provincial People’s Hospital, Chengdu, 610072, China

    Qin Chen

Authors
  1. Hongmei Tian
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  2. Bo Peng
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  3. Tianrui Li
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  4. Qin Chen
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Corresponding author

Correspondence to Bo Peng .

Editor information

Editors and Affiliations

  1. College of Computer and Software Engineering, Shenzhen University, Shenzhen, China

    Zhenkun Wen

  2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

    Tianrui Li

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Tian, H., Peng, B., Li, T., Chen, Q. (2014). A Novel Graph Cut Algorithm for Weak Boundary Object Segmentation. In: Wen, Z., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54924-3_25

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  • DOI: https://doi.org/10.1007/978-3-642-54924-3_25

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54923-6

  • Online ISBN: 978-3-642-54924-3

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