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A Hierarchical Image Segmentation Algorithm Based on an Observation Scale

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Abstract

Hierarchical image segmentation provides a region-oriented scale-space,i.e., a set of image segmentations at different detail levels in which the segmentations at finer levels are nested with respect to those at coarser levels. Most image segmentation algorithms, such as region merging algorithms, rely on a criterion for merging that does not lead to a hierarchy. In addition, for image segmentation, the tuning of the parameters can be difficult. In this work, we propose a hierarchical graph based image segmentation relying on a criterion popularized by Felzenszwalb and Huttenlocher. Quantitative and qualitative assessments of the method on Berkeley image database shows efficiency, ease of use and robustness of our method.

The authors are grateful to FAPEMIG and CAPES, which are Brazilian research funding agencies, and also to Agence Nationale de la Recherche through contract ANR-2010-BLAN-0205-03 KIDICO, which is a French research funding agency.

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References

  1. Zahn, C.T.: Graph-theoretical methods for detecting and describing gestalt clusters. IEEE Trans. Comput. 20, 68–86 (1971)

    Article MATH  Google Scholar 

  2. Morris, O., Lee, M.J., Constantinides, A.: Graph theory for image analysis: an approach based on the shortest spanning tree. Communications, Radar and Signal Processing, IEE Proceedings F 133(2), 146–152 (1986)

    Article  Google Scholar 

  3. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation. IJCV 59, 167–181 (2004)

    Article  Google Scholar 

  4. Najman, L.: On the equivalence between hierarchical segmentations and ultrametric watersheds. JMIV 40, 231–247 (2011)

    Article MathSciNet  Google Scholar 

  5. Cousty, J., Najman, L.: Incremental Algorithm for Hierarchical Minimum Spanning Forests and Saliency of Watershed Cuts. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds.) ISMM 2011. LNCS, vol. 6671, pp. 272–283. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  6. Guigues, L., Cocquerez, J.P., Men, H.L.: Scale-sets image analysis. IJCV 68(3), 289–317 (2006)

    Article  Google Scholar 

  7. Haxhimusa, Y., Kropatsch, W.: Segmentation Graph Hierarchies. In: Fred, A., Caelli, T.M., Duin, R.P.W., Campilho, A.C., de Ridder, D. (eds.) SSPR&SPR 2004. LNCS, vol. 3138, pp. 343–351. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Najman, L., Schmitt, M.: Geodesic saliency of watershed contours and hierarchical segmentation. PAMI 18(12), 1163–1173 (1996)

    Article  Google Scholar 

  9. Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour detection and hierarchical image segmentation. PAMI 33, 898–916 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. PUC Minas - ICEI - DCC - VIPLAB, Brazil

    Silvio Jamil F. Guimarães

  2. Université Paris-Est, LIGM, ESIEE - UPEMLV - CNRS, France

    Silvio Jamil F. Guimarães, Jean Cousty, Yukiko Kenmochi & Laurent Najman

Authors
  1. Silvio Jamil F. Guimarães
  2. Jean Cousty
  3. Yukiko Kenmochi
  4. Laurent Najman

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Auckland, Private Bag 92019, 1142, Auckland, New Zealand

    Georgy Gimel’farb

  2. Department of Computer Science, University of York, Deramore Lane, YO10 5GH, York, UK

    Edwin Hancock

  3. Institute of Media and Information Technology, Chiba University, Yayoi-cho 1-33, 263-8522, Inage-ku, Chiba, Japan

    Atsushi Imiya

  4. Technische Universität/Fraunhofer IGD, Fraunhoferstraße 5, 64283, Darmstadt, Germany

    Arjan Kuijper

  5. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan

    Mineichi Kudo

  6. Graduate School of Engineering, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, 980-8579, Sendai, Miyagi, Japan

    Shinichiro Omachi

  7. Centre for Vision, Speech and Signal Processing, University of Surrey, GU2 7XH, Guildford, Surrey, UK

    Terry Windeatt

  8. C&C Innovation Research Laboratories, NEC Corporation, 8916-47 Takayama-cho, Ikoma-Shi, Nara, Japan

    Keiji Yamada

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© 2012 Springer-Verlag Berlin Heidelberg

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Guimarães, S.J.F., Cousty, J., Kenmochi, Y., Najman, L. (2012). A Hierarchical Image Segmentation Algorithm Based on an Observation Scale. In: Gimel’farb, G.,et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2012. Lecture Notes in Computer Science, vol 7626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34166-3_13

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