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A Graph-Based Approach for Image Segmentation

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Book cover Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5358))

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Abstract

We present a novel graph-based approach to image segmentation. The objective is to partition images such that nearby pixels with similar colors or greyscale intensities belong to the same segment. A graph representing an image is derived from the similarity between the pixels and partitioned by a computationally efficient graph clustering method, which identifies representative nodes for each cluster and then expands them to obtain complete clusters of the graph. Experiments with synthetic and natural images are presented. A comparison with the well known graph clustering method of normalized cuts shows that our approach is faster and produces segmentations that are in better agreement with visual assessment on original images.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Rutgers University, Piscataway, NJ 08854, USA

    Thang V. Le & Casimir A. Kulikowski

  2. DIMACS, Rutgers University, Piscataway, NJ 08854, USA

    Ilya B. Muchnik

Authors
  1. Thang V. Le
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  2. Casimir A. Kulikowski
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  3. Ilya B. Muchnik
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

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© 2008 Springer-Verlag Berlin Heidelberg

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Le, T.V., Kulikowski, C.A., Muchnik, I.B. (2008). A Graph-Based Approach for Image Segmentation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_27

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  • DOI: https://doi.org/10.1007/978-3-540-89639-5_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89638-8

  • Online ISBN: 978-3-540-89639-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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