Skip to main content

Graphics Recognition and Validation Protocol

  • Chapter
  • First Online:
Document Image Analysis
  • 427 Accesses

Abstract

This chapter provides a fundamental study on graphics recognition systems. It basically includes data acquisition and processing to data representation, recognition, retrieval, and spotting. Further, depending on datasets and their availability (for research purpose), and the way we validate the graphics recognition systems (validation protocol).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. A.K. Chhabra, Graphic symbol recognition: an overview, in Proceedings of 2nd International Workshop on Graphics Recognition, Nancy (France) (1997), pp. 244–252

    Google Scholar 

  2. D.S. Doermann, An introduction to vectorization and segmentation, in Tombre, Chhabra [90], pp. 1–8

    Google Scholar 

  3. R. Kasturi, R. Raman, C. Chennubhotla, L. O’Gorman, 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) (1990), pp. 192–230

    Google Scholar 

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

    Article  Google Scholar 

  5. J. Lladós, E. Martí, J.J. Villanueva, 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 

  6. S. Loncaric, A survey of shape analysis techniques. Pattern Recognit. 31(8), 983–1001 (1998)

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Ø.D. Trier, T. Taxt, Evaluation of binarization methods for document images. IEEE Trans. Pattern Anal. Mach. Intell. 17(3), 312–315 (1995)

    Article  Google Scholar 

  9. J. Sauvola, M. Pietikäinen, Adaptive document image binarization. Pattern Recognit. 33(2), 225–236 (2000)

    Article  Google Scholar 

  10. U. Garain, T. Paquet, L. Heutte, On foreground-background separation in low quality document images. Int. J. Doc. Anal. Recognit. 8(1), 47–63 (2006)

    Article  Google Scholar 

  11. T. Taxt, P.J. Flynn, A.K. Jain, Segmentation of Document Images. IEEE Trans. Pattern Anal. Mach. Intell. 11(12), 1322–1329 (1989)

    Article  Google Scholar 

  12. S. Ablameyko, O. Okun, Text separation from graphics based on compactness and area properties. Mach. Graph. Vis. 3(3), 531–541 (1994)

    Google Scholar 

  13. H. Luo, R. Kasturi, Improved directional morphological operations for separation of characters from maps/graphics, in Tombre, Chhabra [90], pp. 35–47

    Google Scholar 

  14. L. Wenyin, D. Dori, A proposed scheme for performance evaluation of graphics/text separation algorithms, in Tombre, Chhabra [90], pp. 359–371

    Google Scholar 

  15. R. Cao, C.L. Tan, Text/graphics separation, in maps, in Graphics Recognition - Algorithms and Applications, ed. by D. Blostein, Y.-B. Kwon, Lecture Notes, in Computer Science, vol. 2390, (Springer, Berlin, 2002), pp. 167–177

    Google Scholar 

  16. R. Cao, C.L. Tan, Separation of overlapping text from graphics, in Proceedings of the 6th International Conference on Document Analysis and Recognition, Seattle, WA (USA) (2001), pp. 44–48

    Google Scholar 

  17. K. Tombre, S. Tabbone, L. Pélissier, B. Lamiroy, Ph. Dosch. Text/graphics separation revisited, in Proceedings of the 5th IAPR International Workshop on Document Analysis Systems, Princeton, NJ (USA), ed. by D. Lopresti, J. Hu, R. Kashi. Lecture Notes in Computer Science, vol. 2423 (Springer, Berlin, 2002), pp. 200–211

    Google Scholar 

  18. A. Velázquez, S. Levachkine, Text/graphics separation and recognition in raster-scanned color cartographic maps, in Proceedings of 5th IAPR International Workshop on Graphics Recognition, Barcelona (Spain) (2003), pp. 92–103

    Google Scholar 

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

    Article  Google Scholar 

  20. D. Doermann, K. Tombre, Handbook of Document Image Processing and Recognition (Springer, New York Incorporated, 2014)

    Book  Google Scholar 

  21. L.A. Fletcher, R. Kasturi, 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 

  22. T.H. DO, Sparse representation over learned dictionary for document analysis. Ph.D. thesis, LORIA, Université de Lorraine, France (2014)

    Google Scholar 

  23. J. Lladós, E. Valveny, G. Sánchez, E. Martí, Symbol recognition: current advances and perspectives, in Graphics Recognition - Algorithms and Applications, ed. by D. Blostein, Y.-B. Kwon, Lecture Notes, in Computer Science, vol. 2390, (Springer, Berlin, 2002), pp. 104–127

    Google Scholar 

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

    Article  Google Scholar 

  25. L.P. Cordella, M. Vento. Symbol and shape recognition, in Proceedings of 3rd International Workshop on Graphics Recognition, Jaipur (India) (1999), pp. 179–186

    Google Scholar 

  26. S. Watanabe, Pattern Recognition: Human and Mechanical (Wiley, New York, 1985). ISBN 0471808156

    Google Scholar 

  27. J. Kittler, Statistical pattern recognition: the state of the art, in Image Analysis and Processing, ed. by V. Cantoni, V. Di Gesù, S. Levialdi, vol. 2, (Plenum Press, New York, 1987), pp. 57–66

    Google Scholar 

  28. S. Raudys, A.K. Jain, Small sample size effects in statistical pattern recognition: recommandations for practitioners. IEEE Trans. Pattern Anal. Mach. Intell. 13(1), 252–264 (1991)

    Article  Google Scholar 

  29. K. Fukunaga, Statistical pattern recognition, in Chen et al. [91], Chap. 1.2, pp. 33–60

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  31. T. Pavlidis, Struct. Pattern Recognit. (Springer, New York, 1980)

    Google Scholar 

  32. W.J. Christmas, J. Kittler, M. Petrou, Structural matching in computer vision using probabilistic relaxation. IEEE Trans. Pattern Anal. Mach. Intell. 17(8), 749–764 (1995)

    Article  Google Scholar 

  33. J. Lladós, E. Martí, Structural recognition of hand drawn floor plans, in 6th Spanish Symposium on Pattern Recognition and Image Analysis, Cordoba (1995), pp. 27–34

    Google Scholar 

  34. V. Claus, H. Ehrig, G. Rozenberg (eds.), Graph-Grammars and Their Applications to Computer Science and Biology (Lecture Notes in Computer Science (Springer, Berlin, 1979)

    Google Scholar 

  35. D. Dori, A. Pnueli, The grammar of dimensions in machine drawings. Comput. Vis. Graph. Image Process. 42, 1–18 (1988)

    Article  Google Scholar 

  36. M. Flasiński, Characteristics of edNLC-Graph Grammar for Syntactic Pattern Recognition. Comput. Vis. Graph. Image Process. 47, 1–21 (1989)

    Article  Google Scholar 

  37. H. Bunke, A. Sanfeliu (eds.), Syntactic and Structural Pattern Recognition (World Scientific, Singapore, 1990)

    MATH  Google Scholar 

  38. H. Bunke, Structural and syntactic pattern recognition, in Chen et al. [91], Chap. 1.5, pp. 163–209

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  40. S. Müller, G. Rigoll, Engineering drawing database retrieval using statistical pattern spotting techniques, in Proceedings of 3rd International Workshop on Graphics Recognition, Jaipur (India) (1999), pp. 219–226

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  42. K.C. Santosh, Character recognition based on dtw-radon, in Proceedings of International Conference on Document Analysis and Recognition (2011), pp. 264–268

    Google Scholar 

  43. K.C. Santosh, B. Lamiroy, L. Wendling, DTW for matching radon features: a pattern recognition and retrieval method, in Advances Concepts for Intelligent Vision Systems (ACIVS) (2011), pp. 249–260

    Google Scholar 

  44. B.T. Messmer, H. Bunke, Efficient error-tolerant subgraph isomorphism detection, in Shape, Structure and Pattern Recognition (Post-proceedings of IAPR Workshop on Syntactic and Structural Pattern Recognition Nahariya, Israel), ed. by D. Dori, A. Bruckstein (World Scientific, Singapore, 1995), pp. 231–240

    Google Scholar 

  45. J.-Y. Ramel, G. Boissier, H. Emptoz. A structural representation adapted to handwritten symbol recognition, in Proceedings of 3rd International Workshop on Graphics Recognition, Jaipur (India) (1999), pp. 259–266

    Google Scholar 

  46. J.Y. Ramel, N. Vincent, H. Emptoz, A structural representation for understanding line-drawing images. Int. J. Doc. Anal. Recognit. 3(2), 58–66 (2000)

    Article  Google Scholar 

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

    Google Scholar 

  48. K.C. Santosh, B. Lamiroy, L. Wendling, Spatio-structural symbol description with statistical feature add-on, in Graphics Recognition. New Trends and Challenges, ed. by Y.-B. Kwon, J.-M. Ogier, Lecture Notes, in Computer Science, vol. 7423, (Springer, Berlin, 2011), pp. 228–237

    Chapter  Google Scholar 

  49. K.C. Santosh, Reconnaissance graphique en utilisant les relations spatiales et analyse de la forme. (Graphics Recognition using Spatial Relations and Shape Analysis). Ph.D. thesis, University of Lorraine, France (2011)

    Google Scholar 

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

    Article  Google Scholar 

  51. K.C. Santosh, L. Wendling, B. Lamiroy, Relation bag-of-features for symbol retrieval, in 12th International Conference on Document Analysis and Recognition (2013), pp. 768–772

    Google Scholar 

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

    Article  Google Scholar 

  53. K.C. Santosh, L. Wendling, Bor: bag-of-relations for symbol retrieval. Int. J. Pattern Recognit. Artif. Intell. 28(06), 1450017 (2014)

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  56. L.P. Cordella, P. Foggia, R. Genna, M. Vento, Prototyping structural descriptions: an inductive learning approach, in Advances in Pattern Recognition (Proceedings of Joint IAPR Workshops SSPR’98 and SPR’98, Sydney, Australia), ed. by A. Amin, D. Dori, P. Pudil, H. Freeman. Lecture Notes in Computer Science, vol. 1451 (1998), pp. 339–348

    Chapter  Google Scholar 

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

    Google Scholar 

  58. H.S. Baird, Feature identification for hybrid structural/statistical pattern classification. Comput. Vis. Graph. Image Process. 42, 318–333 (1988)

    Article  Google Scholar 

  59. K.S. Fu, A step towards unification of syntactic and statistical pattern recognition. IEEE Trans. Pattern Anal. Mach. Intell. 5(2), 200–205 (1983)

    MATH  Google Scholar 

  60. L. Miclet, Grammatical inference, in Syntactic and Structural Pattern Recognition: Theory and Applications (Chap. 9), ed. by H. Bunke, A. Sanfeliu (World Scientific, Singapore, 1990), pp. 237–290

    Chapter  Google Scholar 

  61. S. Satoh, T. Satou, M. Sakauchi, One Method of Structural Description Rule Extraction based on Graphical and Spatial Relations. 2, 281–284 (1992)

    Google Scholar 

  62. K. Tombre, Structural and syntactic methods in line drawing analysis: to which extent do they work? in Advances in Structural and Syntactial Pattern Recognition (Proceedings of 6th International SSPR Workshop, Leipzig, Germany), ed. by P. Perner, P. Wang, A. Rosenfeld. Lecture Notes in Computer Science, vol. 1121 (Springer, Berlin, 1996), pp. 310–321

    Chapter  Google Scholar 

  63. J. Lladós, G. Sánchez, E. Martí, A string based method to recognize symbols and structural textures in architectural plans, in Proceedings of 2nd International Workshop on Graphics Recognition, Nancy (France) (1997), pp. 287–294

    Google Scholar 

  64. B. Lamiroy, D.P. Lopresti, H.F. Korth, J. Heflin, 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 (2011), p. 78740O

    Google Scholar 

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

    Google Scholar 

  66. B. Lamiroy, D.P. Lopresti, The non-geek’s guide to the DAE platform, in 10th IAPR International Workshop on Document Analysis Systems (2012), pp. 27–32

    Google Scholar 

  67. B. Lamiroy, D.P. Lopresti, The DAE platform: a framework for reproducible research in document image analysis, in Reproducible Research in Pattern Recognition - First International Workshop, RRPR@ICPR 2016, Revised Selected Papers (2016), pp. 17–29

    Chapter  Google Scholar 

  68. B. Lamiroy, DAE-NG: a shareable and open document image annotation data framework, in 1st International Workshop on Open Services and Tools for Document Analysis, 14th IAPR International Conference on Document Analysis and Recognition (2017), pp. 31–34

    Google Scholar 

  69. R.M. Haralick, Performance evaluation of document image algorithms, in Graphics Recognition-Recent Advances, ed. by A.K. Chhabra, D. Dori, Lecture Notes, in Computer Science, vol. 1941, (Springer, Berlin, 2000), pp. 315–323

    Chapter  Google Scholar 

  70. Ihsin T. Phillips, Jisheng Liang, Atul K. Chhabra, Robert M. Haralick, A performance evaluation protocol for graphics recognition systems, in Algorithms and Systems, ed. by Graphics Recognition (Second International Workshop, Selected Papers, 1997), pp. 372–389

    Google Scholar 

  71. M. Delalandre, J.-Y. Ramel, N. Sidere, A semi-automatic groundtruthing framework for performance evaluation of symbol recognition and spotting systems. Lecture Notes in Computer Science, vol. 7423 (Springer, Berlin, 2013), pp. 163–172

    Chapter  Google Scholar 

  72. M. Delalandre, E. Valveny, T. Pridmore, D. Karatzas, Generation of synthetic documents for performance evaluation of symbol recognition & spotting systems. Int. J. Do. Anal. Recognit. 13(3), 187–207 (2010)

    Article  Google Scholar 

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

    Google Scholar 

  74. M. Delalandre, J.-Y. Ramel, E. Valveny, M.M. Luqman, A performance characterization algorithm for symbol localization, in Graphics Recognition. Achievements, Challenges, and Evolution, 8th International Workshop, Selected Papers (2009), pp. 260–271

    Google Scholar 

  75. E. Valveny, M. Delalandre, R. Raveaux, B. Lamiroy, Report on the symbol recognition and spotting contest, in Graphics Recognition. New Trends and Challenges - 9th International Workshop, Revised Selected Papers (2011), pp. 198–207

    Chapter  Google Scholar 

  76. FRESH. Final report on symbol recognition with evaluation of performances. Deliverable 2.4.2. - FP6-516059 (2007)

    Google Scholar 

  77. W. Liu, D. Dori, Incremental arc segmentation algorithm and its evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 20(4), 424–431 (1998)

    Article  Google Scholar 

  78. S. Song, M.-R. Lyu, S. Cai, Effective multiresolution arc segmentation: algorithms and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 16(11), 1491–1506 (2004)

    Article  Google Scholar 

  79. K.S. Beyer, J. Goldstein, R. Ramakrishnan, U. Shaft, When is “nearest neighbor” meaningful? in Proceedings of International Conference on Database Theory (Springer, London, 1999), pp. 217–235

    Google Scholar 

  80. E.H. Barney Smith, An analysis of binarization ground truthing, in Proceedings of International Workshop on Document Analysis Systems (ACM, New York, 2010), pp. 27–34

    Google Scholar 

  81. T.B. Sebastian, P.N. Klein, B.B. Kimia, Recognition of shapes by editing shock graphs, in Proceedings of International Conference on Computer Vision (2001), pp. 755–762

    Google Scholar 

  82. J. Rendek, L. Wendling, On determining suitable subsets of decision rules using choquet integral. Int. J. Pattern Recognit. Artif. Intell. 22(2), 207–232 (2008)

    Article  Google Scholar 

  83. L.J. Latecki, R. Lakmper, U. Eckhardt, Shape descriptors for non-rigid shapes with a single closed contour, in Computer Vision and Pattern Recognition (2000), pp. 1424–1429

    Google Scholar 

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

    Article  Google Scholar 

  85. C. Grigorescu, N. Petkov, Distance sets for shape filters and shape recognition. IEEE Trans. Image Process. 12(10), 1274–1286 (2003)

    Article  MathSciNet  Google Scholar 

  86. T.B. Sebastian, P.N. Klein, B.B. Kimia, On aligning curves. IEEE Trans. Pattern Anal. Mach. Intell. 25(1), 116–125 (2003)

    Article  Google Scholar 

  87. B.M. Mehtre, M.S. Kankanhalli, A.D. Narasimhalu, G.C. Man, Color matching for image retrieval. Pattern Recognit. Lett. 16(3), 325–331 (1995)

    Article  Google Scholar 

  88. B. Lamiroy, T. Sun, Computing precision and recall with missing or uncertain ground truth, in Graphics Recognition. New Trends and Challenge, ed. by Y.-B. Kwon, J.-M. Ogier, Lecture Notes, in Computer Science, vol. 7423, (Springer, Berlin, 2013), pp. 149–162

    Chapter  Google Scholar 

  89. B. Lamiroy, On the limits of machine perception and interpretation. (Sur les limites de la perception artificielle et de l’interprétation) (2013)

    Google Scholar 

  90. K. Tombre, A.K. Chhabra (eds.), Graphics Recognition—Algorithms and Systems. Lecture Notes in Computer Science, vol. 1389 (Springer, Berlin, 1998)

    Google Scholar 

  91. C.H. Chen, L.F. Pau, P.S.P. Wang (eds.), Handbook of Pattern Recognition and Computer Vision (World Scientific, Singapore, 1993)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. C. Santosh .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Santosh, K.C. (2018). Graphics Recognition and Validation Protocol. In: Document Image Analysis. Springer, Singapore. https://doi.org/10.1007/978-981-13-2339-3_3

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-2339-3_3

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2338-6

  • Online ISBN: 978-981-13-2339-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics