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Generative Multi-region Segmentation by Utilizing Saliency Information

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Book cover Biometric Recognition (CCBR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10568))

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Abstract

In traditional method, multi-region segmentation is treated as a pre-operation process of semantic method. A method for automatically partitioning an image into multiple regions is presented in this paper. Motivated by the observation that saliency information can exhibit plentiful meaningful cues for segmentation, we propose a semi-supervised multi-region segmentation method in this paper. Saliency features are applied for seeds location together with color information, then the multiregion segmentation problem is solved using a generative semi-supervised framework in which the selected seeds are treated as initializations. The segmentation results are further refined using a segmentation composition strategy. We demonstrate the effectiveness of our algorithm against the state-of-the-art methods on the benchmark Berkley segmentation dataset.

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Author information

Authors and Affiliations

  1. University of Shanghai for Science and Technology, JunGong Road NO. 516, Shanghai, China

    Lei Zhou & Yubin Xia

Authors
  1. Lei Zhou
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  2. Yubin Xia
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Corresponding author

Correspondence to Lei Zhou .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Computing and Technology, Chinese Academy of Sciences, Beijing, China

    Yong Xu

  5. Shenzhen University, Shenzhen, China

    Linlin Shen

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

  7. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  8. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yu Qiao

  9. Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Zhenhua Guo

  10. Shenzhen University, Shenzhen, China

    Shiqi Yu

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Zhou, L., Xia, Y. (2017). Generative Multi-region Segmentation by Utilizing Saliency Information. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_75

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  • DOI: https://doi.org/10.1007/978-3-319-69923-3_75

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69922-6

  • Online ISBN: 978-3-319-69923-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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