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Unsupervised Image Segmentation with Fuzzy Connectedness

  • Conference paper
PRICAI 2004: Trends in Artificial Intelligence (PRICAI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3157))

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Abstract

In this paper, we report a method to do unsupervised image segmentations based on fuzzy connectedness with scale space theory. A new measure for doing segmented regions’ mergence is also proposed. The method can be used in many applications like content based image retrieval and medical image analysis, etc.

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References

  1. Saha, P.K., Udupa, J.K.: Iterative relative fuzzy connectedness and object definition: Theory, algorithms, and application in image segmentation. In: Proceedings of IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. Hilton Head, pp. 28–35 (2000)

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  2. Tang, M., Ma, S.: General scheme of region competition based on scale space. IEEE Trans. PAMI 23, 1366–1378 (2001)

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Author information

Authors and Affiliations

  1. Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, 200030, China

    Yuanjie Zheng, Jie Yang & Yue Zhou

Authors
  1. Yuanjie Zheng
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  2. Jie Yang
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  3. Yue Zhou
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Department of Computer Science, Auckland University of Technology, 1020, Auckland, New Zealand

    Hans W. Guesgen

  3. Artificial Intelligence Technology Centre, Auckland University of Technology, Auckland, New Zealand

    Wai-Kiang Yeap

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© 2004 Springer-Verlag Berlin Heidelberg

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Zheng, Y., Yang, J., Zhou, Y. (2004). Unsupervised Image Segmentation with Fuzzy Connectedness. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_114

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  • DOI: https://doi.org/10.1007/978-3-540-28633-2_114

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22817-2

  • Online ISBN: 978-3-540-28633-2

  • eBook Packages: Springer Book Archive

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