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Multivalent Graph Matching for Symbol Recognition

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Book cover Document Analysis and Recognition – ICDAR 2021 Workshops (ICDAR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12917))

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Abstract

This paper deals with a symbol recognition problem where symbols are deformed in different ways. To address this difficulty, the multivalent graph matching problem is considered to allow more matching possibilities between the symbols. More precisely, a solution to the multivalent graph matching problem is formulated as an extended graph edit distance minimum with additional splitting and merging operations. This minimization problem is tackled with a variant of ant colony optimization, the max-min ant system. Besides, a neighborhood search strategy added to the solution building process of the max-min ant system aims to accelerate the computational time. The efficiency of the proposed approach is illustrated in a symbol dataset in several aspects, covering both quality and quantity analyses. The result shows the interest in using multivalent graph matching to deal with noisy symbols and their meaningful interpretability in the context of sub-part correspondence against other bijective graph matching-based approaches.

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Notes

  1. 1.

    Can be accessed here: http://mathieu.delalandre.free.fr/projects/sesyd/.

References

  1. Ambauen, R., Fischer, S., Bunke, H.: Graph edit distance with node splitting and merging, and its application to diatom identification. In: GbRPR, pp. 95–106 (2003)

    Google Scholar 

  2. Berretti, S., Bimbo, A.D., Pala, P.: Graph edit distance for active graph matching in content based retrieval applications. Open Artif. Intell. J. 1(1) (2007)

    Google Scholar 

  3. Berretti, S., Del Bimbo, A., Pala, P.: A graph edit distance based on node merging. In: ICIVR, pp. 464–472 (2004)

    Google Scholar 

  4. Boeres, M.C., Ribeiro, C.C., Bloch, I.: A randomized heuristic for scene recognition by graph matching. In: International Workshop on Experimental and Efficient Algorithms, pp. 100–113 (2004)

    Google Scholar 

  5. Bunke, H., Riesen, K.: Recent advances in graph-based pattern recognition with applications in document analysis. Pattern Recogn. 44(5), 1057–1067 (2011)

    Article  Google Scholar 

  6. Conte, D., Foggia, P., Sansone, C., Vento, M.: Graph matching applications in pattern recognition and image processing. In: IEEE ICIP, vol. 2, pp. II-21 (2003)

    Google Scholar 

  7. Conte, D., Foggia, P., Sansone, C., Vento, M.: Thirty years of graph matching in pattern recognition. IJPRAI 18(03), 265–298 (2004)

    Google Scholar 

  8. Fischer, S., Gilomen, K., Bunke, H.: Identification of diatoms by grid graph matching. In: S+SSPR, pp. 94–103 (2002)

    Google Scholar 

  9. Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE SMC 4(2), 100–107 (1968)

    Google Scholar 

  10. Ho, K.D., Ramel, J., Monmarché, N.: Multivalent graph matching problem solved by max-min ant system. In: S+SSPR, pp. 227–237 (2020)

    Google Scholar 

  11. Lades, M., et al.: Distortion invariant object recognition in the dynamic link architecture. IEEE Trans. Comput. 42(3), 300–311 (1993)

    Article  Google Scholar 

  12. Neuhaus, M., Riesen, K., Bunke, H.: Fast suboptimal algorithms for the computation of graph edit distance. In: S+SSPR, pp. 163–172 (2006)

    Google Scholar 

  13. Noma, A., Pardo, A., Cesar, R.M., Jr.: Structural matching of 2D electrophoresis gels using deformed graphs. Pattern Recogn. Lett. 32(1), 3–11 (2011)

    Article  Google Scholar 

  14. Qureshi, R.J., Ramel, J.Y., Cardot, H., Mukherji, P.: Combination of symbolic and statistical features for symbols recognition. In: ICSPCN, pp. 477–482 (2007)

    Google Scholar 

  15. Riesen, K., Bunke, H.: Approximate graph edit distance computation by means of bipartite graph matching. Image Vis. Comput. 27(7), 950–959 (2009)

    Article  Google Scholar 

  16. Sammoud, O., Solnon, C., Ghédira, K.: Ant algorithm for the graph matching problem. In: EvoCOP, pp. 213–223 (2005)

    Google Scholar 

  17. Sammoud, O., Sorlin, S., Solnon, C., Ghédira, K.: A comparative study of ant colony optimization and reactive search for graph matching problems. In: EvoCOP, pp. 234–246 (2006)

    Google Scholar 

  18. Shokoufandeh, A., Dickinson, S.: A unified framework for indexing and matching hierarchical shape structures. In: IWVF, pp. 67–84 (2001)

    Google Scholar 

  19. Sorlin, S., Solnon, C., Jolion, J.M.: A generic graph distance measure based on multivalent matchings. In: Kandel, A., Bunke, H., Last, M. (eds.) Applied Graph Theory in Computer Vision and Pattern Recognition, pp. 151–181. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-68020-8_6

  20. Stauffer, M., Fischer, A., Riesen, K.: Filters for graph-based keyword spotting in historical handwritten documents. Pattern Recogn. Lett. 134, 125–134 (2020)

    Article  Google Scholar 

  21. Stützle, T., Hoos, H.H.: Max-min ant system. Future Gener. Comput. Syst. 16(8), 889–914 (2000)

    Article  Google Scholar 

  22. Tefas, A., Kotropoulos, C., Pitas, I.: Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication. IEEE PAMI 23(7), 735–746 (2001)

    Article  Google Scholar 

  23. Zaslavskiy, M., Bach, F., Vert, J.P.: A path following algorithm for the graph matching problem. IEEE PAMI 31(12), 2227–2242 (2008)

    Article  Google Scholar 

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Authors and Affiliations

  1. Laboratoire d’Informatique Fondamentale et Appliquée de Tours, Université de Tours, Tours, France

    D. K. Ho, J. Y. Ramel & N. Monmarché

Authors
  1. D. K. Ho
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  2. J. Y. Ramel
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  3. N. Monmarché
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Corresponding author

Correspondence to D. K. Ho .

Editor information

Editors and Affiliations

  1. Boise State University, Boise, ID, USA

    Elisa H. Barney Smith

  2. Indian Statistical Institute, Kolkata, India

    Umapada Pal

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Ho, D.K., Ramel, J.Y., Monmarché, N. (2021). Multivalent Graph Matching for Symbol Recognition. In: Barney Smith, E.H., Pal, U. (eds) Document Analysis and Recognition – ICDAR 2021 Workshops. ICDAR 2021. Lecture Notes in Computer Science(), vol 12917. Springer, Cham. https://doi.org/10.1007/978-3-030-86159-9_35

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  • DOI: https://doi.org/10.1007/978-3-030-86159-9_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86158-2

  • Online ISBN: 978-3-030-86159-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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