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A K-Means Shape Classification Algorithm Using Shock Graph-Based Edit Distance

  • Conference paper
Communication and Networking (FGCN 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 120))

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Abstract

Skeleton is a very important feature for shape-based image classification. In this paper, we apply the discrete shock graph-based skeleton features to classify shapes into predefined groups, using a k-means clustering algorithm. The graph edit cost obtained by transforming database image graph into the respected query graph, will be used as distance function for the k-means clustering. To verify the performance of the suggested algorithm, we tested it on MPEG-7 dataset and our algorithm shows excellent performance for shape classification.

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References

  1. Sebastian, T.B., Klein, P.N., Kimia, B.B.: Recognition of Shapes by Editing Their Shock Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 26(5), 550–571 (2004)

    Article  Google Scholar 

  2. Bai, X., Latecki, L.J.: Path Similarity Skeleton Graph Matching. IEEE Trans. Pattern Anal. Mach. Intell. 30(7), 1282–1292 (2008)

    Article  Google Scholar 

  3. Zaboli, H., Rahmati, M.: An Improved Shock Graph Approach for Shape Recognition and Retrieval. In: Proc. First Asia Int. Conf. on Modelling and Simulation, Thailand, pp. 438–443 (March 2007)

    Google Scholar 

  4. Goh, W.-B.: Strategies for Shape Matching Using Skeletons. Comput. Vis. Image Underst. 110(3), 326–345 (2008)

    Article  Google Scholar 

  5. Khanam, S., Jang, S.W., Paik, W.: An Improved Shock Graph-Based Edit Distance Approach Using an Adaptive Weighting Scheme. CCIS, vol. 56, pp. 501–508. Springer, Heidelberg (2009)

    Google Scholar 

  6. Khanam, S., Jang, S.W., Paik, W.: Fast and Simple 2D Shape Retrieval Using Discrete Shock Graph. Electron. Lett. (submitted, 2010)

    Google Scholar 

  7. MacQueen, J.B.: Some Methods for Classification and Analysis of Multivariate Observations. In: Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press, Berkeley (1967)

    Google Scholar 

  8. Cheung, Y.M.: k*-Means: A New Generalized k-means Clustering Algorithm. Pattern Recognit. Lett. 24, 2883–2893 (2003)

    Article  MATH  Google Scholar 

  9. ImageProcessingPlace, http://www.imageprocessingplace.com/root_files_V3/image_databases.htLoudon

  10. Blum, H.: A Transformation for Extracting New Descriptors of Shape. W. Whaten-Dunn, MIT Press (1967)

    Google Scholar 

  11. Nasreddine, K., Benzinou, A., Fablet, R.: Variational shape matching for shape classification and retrieval. Pattern Recognit. Lett. 31, 1650–1657 (2010)

    Article  Google Scholar 

  12. Kim, W.Y., Kim, Y.S.: A region-based shape descriptor using Zernike moments. Signal Process.-Image Commun. 16, 95–102 (2000)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, Konkuk University, 322, Danwol-Dong, Chungju-Si, Chungcheongbuk-do, 380-701, Korea

    Solima Khanam & Woojin Paik

  2. Dept. of Digital Media, Anyang University, 708-113, Anyang 5-dong, Manan-gu, Anyang-si, Gyeonggi-do, 430-714, Korea

    Seok-Woo Jang

Authors
  1. Solima Khanam
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  2. Seok-Woo Jang
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  3. Woojin Paik
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Editor information

Editors and Affiliations

  1. Hannam University, Daejeon, South Korea

    Tai-hoon Kim

  2. University of Western Macedonia, Kozani, Greece

    Thanos Vasilakos

  3. Faculty of Information Science and Electrical Engineering, Kyushu University, 6-10-1 Hakozaki, 812-8581, Fukuoka, Japan

    Kouichi Sakurai

  4. The University of Alabama, Tuscaloosa, AL, USA

    Yang Xiao

  5. Sun Yat-sen University, 510275, Guangzhou, P.R. China

    Gansen Zhao

  6. University of Warsaw & Infobright Inc., Poland

    Dominik Ślęzak

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© 2010 Springer-Verlag Berlin Heidelberg

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Khanam, S., Jang, SW., Paik, W. (2010). A K-Means Shape Classification Algorithm Using Shock Graph-Based Edit Distance. In: Kim, Th., Vasilakos, T., Sakurai, K., Xiao, Y., Zhao, G., Ślęzak, D. (eds) Communication and Networking. FGCN 2010. Communications in Computer and Information Science, vol 120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17604-3_29

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  • DOI: https://doi.org/10.1007/978-3-642-17604-3_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17603-6

  • Online ISBN: 978-3-642-17604-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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