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Complex and Composite Graphical Symbol Recognition and Retrieval: A Quick Review

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 709))

Abstract

One of the key difficulties in graphics recognition domain is to work on complex and composite symbol recognition, retrieval and spotting. This paper covers a quick view on complex and composite symbol recognition, which is inspired by real-world industrial problem. Considering it as a pattern recognition problem, three different approaches: statistical, structural and syntactic are taken into account. It includes fundamental concepts or techniques and research standpoints or directions derived by a real-world application.

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References

  1. Adam, S., Ogier, J.M., Cariou, C., Mullot, R., Labiche, J., Gardes, J.: Symbol and character recognition: application to engineering drawings. Int. J. Doc. Anal. Recogn. 3(2), 89–101 (2000)

    Article  MATH  Google Scholar 

  2. Ah-Soon, C., Tombre, K.: Architectural symbol recognition using a network of constraints. Pattern Recogn. Lett. 22(2), 231–248 (2001)

    Article  MATH  Google Scholar 

  3. Almazán, J., Fornés, A., Valveny, E.: A non-rigid appearance model for shape description and recognition. Pattern Recogn. 45(9), 3105–3113 (2012)

    Article  Google Scholar 

  4. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)

    Article  Google Scholar 

  5. Bunke, H., Wang, P.S.P. (eds.): Handbook of Character Recognition and Document Image Analysis. World Scientific, Singapore (1997)

    Google Scholar 

  6. Chaudhuri, B.B., Garain, U.: An approach for recognition and interpretation of mathematical expressions in printed document. Pattern Anal. Appl. 3(2), 120–131 (2000)

    Article  Google Scholar 

  7. Chhabra, A.K.: Graphic symbol recognition: an overview. In: Proceedings of 2nd International Workshop on Graphics Recognition, Nancy, France, pp. 244–252, August 1997

    Google Scholar 

  8. Claus, V., Ehrig, H., Rozenberg, G. (eds.): Graph-Grammars and Their Applications to Computer Science and Biology. LNCS, vol. 73. Springer, Heidelberg (1979)

    Google Scholar 

  9. Cordella, L.P., Foggia, P., Genna, R., Vento, M.: Prototyping structural descriptions: an inductive learning approach. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds.) SSPR /SPR 1998. LNCS, vol. 1451, pp. 339–348. Springer, Heidelberg (1998). doi:10.1007/BFb0033252

    Chapter  Google Scholar 

  10. Cordella, L.P., Vento, M.: Symbol and shape recognition. In: Proceedings of 3rd International Workshop on Graphics Recognition, Jaipur, India, pp. 179–186, September 1999

    Google Scholar 

  11. Cordella, L.P., Vento, M.: Symbol recognition in documents: a collection of techniques? Int. J. Doc. Anal. Recogn. 3(2), 73–88 (2000)

    Article  Google Scholar 

  12. Deans, S.R.: Applications of the Radon Transform. Wiley Interscience Publications, New York (1983)

    MATH  Google Scholar 

  13. Delalandre, M., Ramel, J.-Y., Sidere, N.: A semi-automatic groundtruthing framework for performance evaluation of symbol recognition and spotting systems. In: Kwon, Y.-B., Ogier, J.-M. (eds.) GREC 2011. LNCS, vol. 7423, pp. 163–172. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36824-0_16

    Chapter  Google Scholar 

  14. Delalandre, M., Valveny, E., Lladós, J.: Performance evaluation of symbol recognition and spotting systems: an overview. In: Kise, K., Sako, H. (eds.) Proceedings of International Workshop on Document Analysis Systems, pp. 497–505. IEEE Computer Society (2008)

    Google Scholar 

  15. Delalandre, M., Valveny, E., Pridmore, T., Karatzas, D.: Generation of synthetic documents for performance evaluation of symbol recognition and spotting systems. Int. J. Doc. Anal. Recogn. 13(3), 187–207 (2010)

    Article  Google Scholar 

  16. Devaux, P.M., Lysak, D.B., Kasturi, R.: A complete system for the intelligent interpretation of engineering drawings. Int. J. Doc. Anal. Recogn. 2(2/3), 120–131 (1999)

    Article  Google Scholar 

  17. Doermann, D., Tombre, K.: Handbook of Document Image Processing and Recognition. Springer, London (2014)

    Book  MATH  Google Scholar 

  18. Doermann, D.S.: An introduction to vectorization and segmentation. In: Tombre, K., Chhabra, A.K. (eds.) GREC 1997. LNCS, vol. 1389, pp. 1–8. Springer, Heidelberg (1998). doi:10.1007/3-540-64381-8_34

    Chapter  Google Scholar 

  19. Dori, D., Pnueli, A.: The grammar of dimensions in machine drawings. Computer Vision, Graphics and Image Processing 42, 1–18 (1988)

    Article  Google Scholar 

  20. Dosch, P., Tombre, K., Ah-Soon, C., Masini, G.: A complete system for analysis of architectural drawings. Int. J. Doc. Anal. Recogn. 3(2), 102–116 (2000)

    Article  Google Scholar 

  21. Escalera, S., Fornés, A., Pujol, O., Lladós, J., Radeva, P.: Circular blurred shape model for multiclass symbol recognition. IEEE Trans. Syst. Man Cybern. Part B Cybern. 41(2), 497–506 (2011)

    Article  Google Scholar 

  22. Feng, G., Viard-Gaudin, C., Sun, Z.: On-line hand-drawn electric circuit diagram recognition using 2D dynamic programming. Pattern Recogn. 42(12), 3215–3223 (2009)

    Article  MATH  Google Scholar 

  23. Flasiński, M.: Characteristics of edNLC-graph grammar for syntactic pattern recognition. Comput. Vis. Graph. Image Process. 47, 1–21 (1989)

    Article  Google Scholar 

  24. Fletcher, L.A., Kasturi, R.: A robust algorithm for text string separation from mixed text/graphics images. IEEE Trans. Pattern Anal. Mach. Intell. 10(6), 910–918 (1988)

    Article  Google Scholar 

  25. FRESH: Final report on symbol recognition with evaluation of performances. http://www.aero-scratch.net/fresh.html. Deliverable 2.4.2.-FP6-516059

  26. GREC: International symbol recognition contest at GREC2003 (2003). http://www.cvc.uab.es/grec2003/SymRecContest/

  27. Ha, D.T.: Sparse representation over learned dictionary for document analysis. Ph.D. thesis, LORIA, Université de Lorraine, France (2014)

    Google Scholar 

  28. Heutte, L., Nosary, A., Paquet, T.: A multiple agent architecture for handwritten text recognition. Pattern Recogn. 37(4), 665–674 (2004)

    Article  MATH  Google Scholar 

  29. Jain, A.K., Duin, R.P.W., Mao, J.: Statistical pattern recognition: a review. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 4–37 (2000)

    Article  Google Scholar 

  30. Kasturi, R., Raman, R., Chennubhotla, C., O’Gorman, L.: document image analysis: an overview of techniques for graphics recognition. In: Pre-proceedings of IAPR Workshop on Syntactic and Structural Pattern Recognition, Murray Hill, NJ (USA), pp. 192–230 (1990)

    Google Scholar 

  31. Kasturi, R., O’Gorman, L., Govindaraju, V.: Document image analysis: a primer. Charact. Recogn. 27(1), 3–22 (2002)

    Google Scholar 

  32. Kim, W.Y., Kim, Y.S.: A region-based shape descriptor using Zernike moments. Sig. Process. Image Commun. 16(1–2), 95–102 (2000)

    Article  Google Scholar 

  33. Lamiroy, B., Lopresti, D.P.: An open architecture for end-to-end document analysis benchmarking. In: International Conference on Document Analysis and Recognition, pp. 42–47 (2011)

    Google Scholar 

  34. Lamiroy, B., Lopresti, D.P., Korth, H.F., Heflin, J.: How carefully designed open resource sharing can help and expand document analysis research. In: Document Recognition and Retrieval XVIII, Part of the IS&T-SPIE Electronic Imaging Symposium

    Google Scholar 

  35. Lladós, J., Martí, E., Villanueva, J.J.: Symbol recognition by error-tolerant subgraph matching between region adjacency graphs. IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1137–1143 (2001)

    Article  Google Scholar 

  36. Lladós, J., Valveny, E., Sánchez, G., Martí, E.: Symbol recognition: current advances and perspectives. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, pp. 104–128. Springer, Heidelberg (2002). doi:10.1007/3-540-45868-9_9

    Chapter  Google Scholar 

  37. Lladós, J., Rusiñol, M.: Graphics Recognition Techniques, pp. 489–521. Springer, London (2014)

    Google Scholar 

  38. Loncaric, S.: A survey of shape analysis techniques. Pattern Recogn. 31(8), 983–1001 (1998)

    Article  Google Scholar 

  39. Luqman, M.M.: fuzzy multilevel graph embedding for recognition, indexing and retrieval of graphic document images. Ph.D. thesis, Francois Rabelais University of Tours France and Autonoma University of Barcelona Spain (2012)

    Google Scholar 

  40. Marshall, S.: Review of shape coding techniques. Image Vision Comput. 7(4), 281–294 (1989)

    Article  Google Scholar 

  41. Müller, S., Rigoll, G.: Engineering drawing database retrieval using statistical pattern spotting techniques. In: Proceedings of 3rd International Workshop on Graphics Recognition, Jaipur, India, pp. 219–226, September 1999

    Google Scholar 

  42. Nagy, G.: Twenty years of document image analysis in PAMI. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 38–62 (2000)

    Article  Google Scholar 

  43. Nayef, N.: Geomatric-based symbol spotting and retrieval in technical line drawings. Ph.D. thesis, University of Kaiserslautern, Germany (2012)

    Google Scholar 

  44. Okazaki, A., Kondo, T., Mori, K., Tsunekawa, S., Kawamoto, E.: An automatic circuit diagram reader with loop-structure-based symbol recognition. IEEE Trans. Pattern Anal. Mach. Intell. 10(3), 331–341 (1988)

    Article  Google Scholar 

  45. Qureshi, R.J., Ramel, J.-Y., Barret, D., Cardot, H.: Spotting symbols in line drawing images using graph representations. In: Liu, W., Lladós, J., Ogier, J.-M. (eds.) GREC 2007. LNCS, vol. 5046, pp. 91–103. Springer, Heidelberg (2008). doi:10.1007/978-3-540-88188-9_10

    Chapter  Google Scholar 

  46. Rebelo, A., Capela, G., Cardoso, J.S.: Optical recognition of music symbols: a comparative study. Int. J. Doc. Anal. Recogn. 13(1), 19–31 (2010)

    Article  Google Scholar 

  47. Rendek, J., Masini, G., Dosch, P., Tombre, K.: The search for genericity in graphics recognition applications: design issues of the Qgar software system. In: Marinai, S., Dengel, A.R. (eds.) DAS 2004. LNCS, vol. 3163, pp. 366–377. Springer, Heidelberg (2004). doi:10.1007/978-3-540-28640-0_35

    Chapter  Google Scholar 

  48. Rusiñol, M., Lladós, J.: A performance evaluation protocol for symbol spotting systems in terms of recognition and location indices. Int. J. Doc. Anal. Recogn. 12(2), 83–96 (2009)

    Article  Google Scholar 

  49. Rusiñol, M., Lladós, J.: Symbol Spotting in Digital Libraries: Focused Retrieval over Graphic-rich Document Collections. Springer, London (2010)

    Book  MATH  Google Scholar 

  50. Salmon, J.P.: Reconnaissance de Symboles Complexes. Ph.D. thesis, Institut National Polytechnique de Lorraine (2008)

    Google Scholar 

  51. Samet, H., Soffer, A.: MARCO: map retrieval by content. IEEE Trans. Pattern Anal. Mach. Intell. 18(8), 783–798 (1996)

    Article  Google Scholar 

  52. Santosh, K.C.: Graphics recognition using spatial relations and shape analysis. Ph.D. thesis, INRIA - Institut National Polytechnique de Lorraine, Université de Lorraine, November 2011

    Google Scholar 

  53. Santosh, K.C., Lamiroy, B., Ropers, J.P.: Inductive logic programming for symbol recognition. In: Proceedings of International Conference on Document Analysis and Recognition, pp. 1330–1334. IEEE Computer Society (2009)

    Google Scholar 

  54. K.C., S., Lamiroy, B., Wendling, L.: DTW for matching radon features: a pattern recognition and retrieval method. In: Blanc-Talon, J., Kleihorst, R., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2011. LNCS, vol. 6915, pp. 249–260. Springer, Heidelberg (2011). doi:10.1007/978-3-642-23687-7_23

    Chapter  Google Scholar 

  55. Santosh, K.C., Lamiroy, B., Wendling, L.: Spatio-structural symbol description with statistical feature add-on. In: Kwon, Y.-B., Ogier, J.-M. (eds.) GREC 2011. LNCS, vol. 7423, pp. 228–237. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36824-0_22

    Chapter  Google Scholar 

  56. Santosh, K.C., Lamiroy, B., Wendling, L.: Symbol recognition using spatial relations. Pattern Recog. Lett. 33(3), 331–341 (2012)

    Article  Google Scholar 

  57. Santosh, K.C., Lamiroy, B., Wendling, L.: DTW-radon-based shape descriptor for pattern recognition. Int. J. Pattern Recogn. Artif. Intell. 27(3), 1350008 (2013)

    Article  MathSciNet  Google Scholar 

  58. Santosh, K.C., Lamiroy, B., Wendling, L.: Integrating vocabulary clustering with spatial relations for symbol recognition. Int. J. Doc. Anal. Recogn. 17(1), 61–78 (2014)

    Article  Google Scholar 

  59. Santosh, K.C., Nattee, C., Lamiroy, B.: Relative positioning of stroke-based clustering: a new approach to online handwritten Devanagari character recognition. Int. J. Image Graph. 12(2), 25 (2012)

    Article  MathSciNet  Google Scholar 

  60. Santosh, K.C., Wendling, L.: Character recognition based on non-linear multi-projection profiles measure. Front. Comput. Sci. 9(5), 678–690 (2015)

    Article  Google Scholar 

  61. Santosh, K.C., Wendling, L., Lamiroy, B.: Using spatial relations for graphical symbol description. In: Proceedings of the IAPR International Conference on Pattern Recognition, pp. 2041–2044. IEEE Computer Society (2010)

    Google Scholar 

  62. Santosh, K.C., Wendling, L., Lamiroy, B.: BoR: Bag-of-Relations for symbol retrieval. Int. J. Pattern Recogn. Artif. Intell. 28(06), 1450017 (2014)

    Article  Google Scholar 

  63. Santosh, K., Wendling, L.: Graphical Symbol Recognition, pp. 1–22. Wiley, New York (2015)

    Google Scholar 

  64. Tabbone, S., Terrades, O.R.: An Overview of Symbol Recognition, pp. 523–551. Springer, London (2014)

    Google Scholar 

  65. Tabbone, S., Terrades, O.R., Barrat, S.: Histogram of radon transform. A useful descriptor for shape retrieval. In: Proceedings of the IAPR International Conference on Pattern Recognition, pp. 1–4 (2008)

    Google Scholar 

  66. Tabbone, S., Wendling, L., Salmon, J.P.: A new shape descriptor defined on the radon transform. Comput. Vis. Image Underst. 102(1), 42–51 (2006)

    Article  Google Scholar 

  67. Tabbone, S., Wendling, L., Tombre, K.: Matching of graphical symbols in line-drawing images using angular signature information. Int. J. Doc. Anal. Recogn. 6(2), 115–125 (2003)

    Article  Google Scholar 

  68. Tabbone, S., Wendling, L., Zuwala, D.: A hybrid approach to detect graphical symbols in documents. In: Marinai, S., Dengel, A.R. (eds.) DAS 2004. LNCS, vol. 3163, pp. 342–353. Springer, Heidelberg (2004). doi:10.1007/978-3-540-28640-0_33

    Chapter  Google Scholar 

  69. Terrades, O.R., Tabbone, S., Valveny, E.: A review of shape descriptors for document analysis. In: Proceedings of International Conference on Document Analysis and Recognition, pp. 227–231 (2007)

    Google Scholar 

  70. Tombre, K.: Analysis of engineering drawings: state of the art and challenges. In: Tombre, K., Chhabra, A.K. (eds.) GREC 1997. LNCS, vol. 1389, pp. 257–264. Springer, Heidelberg (1998). doi:10.1007/3-540-64381-8_54

    Chapter  Google Scholar 

  71. Tombre, K.: Ten years of research in the analysis of graphics documents: achievements and open problems. In: Proceedings of 10th Portuguese Conference on Pattern Recognition, Lisbon, Portugal, pp. 11–17, March 1998

    Google Scholar 

  72. Tombre, K., Chhabra, A.K. (eds.): GREC 1997. LNCS, vol. 1389. Springer, Heidelberg (1998). doi:10.1007/3-540-64381-8

    Google Scholar 

  73. Tombre, K.: Graphics recognition: the last ten years and the next ten years. In: Proceedings of 6th IAPR International Workshop on Graphics Recognition, Hong Kong, pp. 422–426 (2005)

    Google Scholar 

  74. Tombre, K.: Graphics recognition - what else? In: Ogier, J.M., Liu, W., Lladós, J. (eds.) Graphics Recognition. Achievements, Challenges, and Evolution. LNCS, vol. 6020, pp. 272–277. Springer, Heidelberg (2010). doi:10.1007/978-3-642-13728-0_25

    Chapter  Google Scholar 

  75. Tombre, K., Lamiroy, B.: Pattern recognition methods for querying and browsing technical documentation. In: Progress in Pattern Recognition, Image Analysis and Applications, 13th Iberoamerican Congress on Pattern Recognition, pp. 504–518 (2008)

    Google Scholar 

  76. Tooley, M., Wyatt, D.: Aircraft electrical and electronic systems: principles, operation and maintenance. Butterworth-Heinemann, Oxford (2008). Aircraft engineering principles and practice

    Google Scholar 

  77. Tsai, W.H., Fu, K.S.: Attributed grammar: a tool for combining syntactic and statistical approaches to pattern recognition. IEEE Trans. Syst. Man Cybern. 10(12), 873–885 (1980)

    Article  MATH  Google Scholar 

  78. Valveny, E., Dosch, P.: Symbol recognition contest: a synthesis. In: Lladós, J., Kwon, Y.-B. (eds.) GREC 2003. LNCS, vol. 3088, pp. 368–385. Springer, Heidelberg (2004). doi:10.1007/978-3-540-25977-0_34

    Chapter  Google Scholar 

  79. Valveny, E., Martí, E.: A model for image generation and symbol recognition through the deformation of lineal shapes. Pattern Recogn. Lett. 24(15), 2857–2867 (2003)

    Article  Google Scholar 

  80. Valveny, E., Tabbone, S., Ramos, O., Philippot, E.: Performance characterization of shape descriptors for symbol representation. In: Liu, W., Lladós, J., Ogier, J.-M. (eds.) GREC 2007. LNCS, vol. 5046, pp. 278–287. Springer, Heidelberg (2008). doi:10.1007/978-3-540-88188-9_26

  81. Wendling, L., Tabbone, S.: A new way to detect arrows in line drawings. IEEE Trans. Pattern Anal. Mach. Intell. 26(7), 935–941 (2004)

    Article  Google Scholar 

  82. Yang, S.: Symbol recognition via statistical integration of pixel-level constraint histograms: a new descriptor. IEEE Trans. Pattern Anal. Mach. Intell. 27(2), 278–281 (2005)

    Article  Google Scholar 

  83. You, K.C., Fu, K.S.: Distorted shape recognition using attributed grammars and error-correcting techniques. Comput. Vis. Graph. Image Process. 13, 1–16 (1980)

    Article  Google Scholar 

  84. Yuen, P.C., Feng, G.C., Tang, Y.Y.: Printed chinese character similarity measurement using ring projection and distance transform. Int. J. Pattern Recogn. Artif. Intell. 12(2), 209–221 (1998)

    Article  Google Scholar 

  85. Zhang, D., Lu, G.: Review of shape representation and description techniques. Pattern Recogn. 37(1), 1–19 (2004)

    Article  Google Scholar 

  86. Zhang, D., Lu, G.: Shape-based image retrieval using generic fourier descriptor. Sig. Process. Image Commun. 17(10), 825–848 (2002)

    Article  Google Scholar 

  87. Zhang, W., Wenyin, L., Zhang, K.: Symbol recognition with kernel density matching. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2020–2024 (2006)

    Article  Google Scholar 

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  1. Department of Computer Science, The University of South Dakota, 414 E Clark Street, Vermillion, SD, 57069, USA

    K. C. Santosh

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  1. K. C. Santosh
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  1. The University of South Dakota, Vermillion, South Dakota, USA

    K.C. Santosh

  2. Karnatak Arts, Science and Commerce College, Bidar, India

    Mallikarjun Hangarge

  3. Polytecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  4. University of Hyderabad, Hyderabad, India

    Atul Negi

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Santosh, K.C. (2017). Complex and Composite Graphical Symbol Recognition and Retrieval: A Quick Review. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_1

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