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Local Structural Analysis: A Primer

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Graphics Recognition. Recent Advances and Perspectives (GREC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3088))

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Abstract

The structural analysis is a processing step during which graphs are extracted from binary images. We can decompose the structural analysis into local and global approaches. The local approach decomposes the connected components, and the global approach groups them together. This paper deals especially with the local structural analysis. The local structural analysis is employed for different applications like symbol recognition, line drawing interpretation, and character recognition. We propose here a primer on the local structural analysis. First, we propose a general decomposition of the local structural analysis into four steps: object graph extraction, mathematical approximation, high-level object construction, and object graph correction. Then, we present some considerations on the method comparison and combination.

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References

  1. Ablameyko, S., Pridmore, T.P.: Machine Interpretation of Line Drawing Images. Springer, Heidelberg (2000)

    Google Scholar 

  2. Ahmed, M., Ward, R.: A Rotation Invariant Rule Based Thinning Algorithm for Character Recognition. Pattern Analysis and Machine Intelligence (PAMI) 24(12), 1672–1678 (2002)

    Article  Google Scholar 

  3. El Badawy, O., Kamel, M.: Shape Representation using Concavity Graphs. In: International Conference on Pattern Recognition, ICPR (2002)

    Google Scholar 

  4. Blostein, D., Fahmy, H., Grbavec, A.: Issues in the Practical Use of Graph Rewriting. In: Cuny, J., Engels, G., Ehrig, H., Rozenberg, G. (eds.) Graph Grammars 1994. LNCS, vol. 1073, pp. 38–55. Springer, Heidelberg (1996)

    Chapter  Google Scholar 

  5. Bodansky, E., Gribov, A., Pilouk, M.: Post-processing of Lines Obtained by Raster-to-Vector Conversion. In: Graphics Recognition, GREC (2001)

    Google Scholar 

  6. Burge, M., Kropatsh, W.G.: A Minimal Line Property Preserving Representation of Line Images. In: Structural and Syntactical Pattern Recognition, SSPR (1998)

    Google Scholar 

  7. Cao, R., Tan, C.L.: A Model of Stroke Extraction from Chinese Character Images. In: International Conference on Pattern Recognition, ICPR (2000)

    Google Scholar 

  8. Chang, F., Lu, Y.C., Palvidis, T.: Feature Analysis Using Line Sweep Thinning Algorithm. Pattern Analysis and Machine Intelligence (PAMI) 21(2), 145–158 (1999)

    Article  Google Scholar 

  9. Chen, Y.S.: Segmentation and Association Among Lines and Junctions for a Line Image. Pattern Recognition (PR) 27(9), 1135–1157 (1994)

    Article  Google Scholar 

  10. Chen, J., Sato, Y., Tamura, S.: Orientation Space Filtering for Multiple Orientation Line Segmentation. Pattern Analysis and Machine Intelligence (PAMI) 22(5), 417–429 (2000)

    Article  Google Scholar 

  11. Chiang, J., Tue, S.: A New Algorithm for Line Image Vectorization. Pattern Recognition (PR) 31(10), 1541–1549 (1998)

    Article  Google Scholar 

  12. Crevier, D., Lepage, R.: Knowledge-Based Image Understanding Systems: A Survey. Computer Vision and Image Understanding (CVIU) 67(2), 161–185 (1997)

    Article  Google Scholar 

  13. Delalandre, M., Nicolas, S., Trupin, E., Ogier, J.M.: Symbols Recognition by Global-Local Structural Approaches, Based on the Scenarios Use, and with a XML Representation of Data. In: International Conference on Document Analysis and Recognition, ICDAR (2003)

    Google Scholar 

  14. Delalandre, M., Saidali, Y., Ogier, J.M., Trupin, E.: Adaptable Vectorisation System Based on Strategic Knowledge and XML Representation Use. In: Lladós, J., Kwon, Y.-B. (eds.) GREC 2003. LNCS, vol. 3088, pp. 199–210. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  15. Doermann, D.: The Indexing and Retrieval Document, a Survey. Technical Report CS-TR-3876, University of Maryland Computer Science Department, USA (1998)

    Google Scholar 

  16. Dori, D.: Sparse Pixel Vectorisation: An Algorithm and its Performance Evaluation. Pattern Analysis and Machine Intelligence (PAMI) 21(3), 202–215 (1999)

    Article  Google Scholar 

  17. Fan, K.C., Wu, W.H.: A Run Length Coding Based Approach to Stroke Extraction of Chinese Characters. Pattern Recognition (PR) 33(11), 1881–1895 (2000)

    Article  MathSciNet  Google Scholar 

  18. Fan, J.: Off-line Optical Character Recognition for Printed Chinese Character-A Survey. Technical Report, University of Colombia, USA (2002)

    Google Scholar 

  19. Hancock, E., Wilson, R.: Graph-Based Methods for Vision: A Yorkist Manifesto. In: Structural and Syntactical Pattern Recognition, SSPR (2002)

    Google Scholar 

  20. Hasan, Y.M.Y., Karan, L.J.: Morphological Reversible Contour Representation. Pattern Analysis and Machine Intelligence (PAMI) 22(3), 227–239 (2000)

    Article  Google Scholar 

  21. Henderson, T.C., Swaminathan, L.: Agent Based Engineering Drawing Analysis. In: Symposium on Document Image Understanding Technology, SDIUT (2003)

    Google Scholar 

  22. Hilaire, X., Tombre, K.: Improving the Accuracy of Skeleton-Based Vectorisation. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, p. 273. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  23. Hilaire, X.: Ranvec and the Arc Segmentation Contest. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, p. 359. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  24. Jain, A.K., Duin, R.P.W., Mao, J.: Statistical Pattern Recognition: a Review. Pattern Analysis and Machine Intelligence (PAMI) 22(1), 4–37 (2000)

    Article  Google Scholar 

  25. Kasturi, R., O’Gorman, L., Govindaraju, V.: Document Image Analysis: A Primer. Sadhana 27(1), 3–22 (2002)

    Article  Google Scholar 

  26. Lam, L., Suen, C.Y.: An Evaluation of Parallel Thinning Algorithms for Character Recognition. Pattern Analysis and Machine Intelligence (PAMI) 17(9), 914–919 (1995)

    Article  Google Scholar 

  27. Lau, K.K., Yuen, P.C., Tang, Y.Y.: Stroke Extraction and Stroke Sequence Estimation On Signatures. In: International Conference on Pattern Recognition, ICDAR (2002)

    Google Scholar 

  28. Lee, C., Wu, B.: A Chinese Character Stroke Extraction Algorithm Based on Contour Information. Pattern Recognition (PR) 31(6), 651–653 (1998)

    Article  Google Scholar 

  29. Lin, X., Shimotsuji, S., Mihoh, M., Sakai, T.: Efficient Diagram Understanding with Characteristic Pattern Detection. Computer Vision Graphics and Image Processing 30, 84–106 (1985)

    Article  Google Scholar 

  30. Lin, F., Tang, X.: Off-line Handwritten Chinese Character Stroke Extraction. In: International Conference on Pattern Recognition, ICPR (2002)

    Google Scholar 

  31. Liu, W., Dori, D.: From Raster to Vectors: Extracting Visual Information from Line Drawings. Pattern Analysis and Applications (PAA) 2(2), 10–21 (1999)

    MATH  Google Scholar 

  32. Lladós, J., Valveny, E., Sánchez, G., Martí, E.: Symbol Recognition: Current Advances an Perspectives. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, p. 104. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  33. Llados, J., Marti, E., Villuanueva, J.J.: Symbol Recognition by Error Subgraph Matching Between Region Adjacency Graphs. Pattern Analysis and Machine Intelligence (PAMI) 23(10), 1137–1143 (2001)

    Article  Google Scholar 

  34. Locarnic, S.: A Survey of Shape Analysis Techniques. Pattern Recognition (PR) 31(8), 983–1001 (1998)

    Article  Google Scholar 

  35. Loo, P.K., Tan, C.L.: Detection of Word Group Based on Irregular Pyramid. In: International Conference on Document Analysis And Recognition, ICDAR (2001)

    Google Scholar 

  36. Loudon, K.: Mastering Algorithms with C. O’Reilly Editions (2000)

    Google Scholar 

  37. Luo, Y., Liu, W.: Engineering Drawings Recognition Using a Case-based Approach. In: International Conference on Document Analysis and Recognition, ICDAR (2003)

    Google Scholar 

  38. Matas, J., Galambos, C., Kittler, J.: Progressive Probabilistic Hough Transform for Line Detection. In: Computer Vision and Pattern Recognition, CVPR (1999)

    Google Scholar 

  39. Nagy, G.: Twenty Years of Document Image Analysis in PAMI. Pattern Analysis and Machine Intelligence (PAMI) 22(1), 38–62 (2000)

    Article  Google Scholar 

  40. Nakajima, Y., Mori, S., Takegami, S., Sato, S.: Global Methods for Stroke Segmentation. International Journal Document Analysis and Recognition (IJDAR) 2, 19–23 (1999)

    Article  Google Scholar 

  41. Neumann, J., Samet, H., Soffer, A.: Integration of Local and Global Shape Analysis for Logo Classification. In: International Workshop on Visual Form, IWVF (2001)

    Google Scholar 

  42. Ogier, J.M., Olivier, C., Lecourtier, Y.: Extraction of Roads from Digitized Maps. In: European Signal Processing Conference, EUSIPCO (1992)

    Google Scholar 

  43. Ogier, J.M., Adam, S., Bessaid, A., Bechar, H.: Automatic Topographic Color Map Analysis System. In: Graphics Recognition, GREC (2001)

    Google Scholar 

  44. Popel, D.V.: Compact Graph Model of Handwritten Images: Integration into Authentification and Recognition. In: Caelli, T.M., Amin, A., Duin, R.P.W., Kamel, M.S., de Ridder, D. (eds.) SPR 2002 and SSPR 2002. LNCS, vol. 2396, p. 272. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  45. Ramel, J.Y., Vincent, N., Emptoz, H.: A Structural Representation for Understanding Line-Drawing Images. International Journal on Document Analysis And Recognition (IJDAR) 3, 58–66 (2000)

    Article  Google Scholar 

  46. Rosin, P.L., West, A.W.: Nonparametric Segmentation of Curves Into Various Representations. Pattern Analysis and Machine Intelligence (PAMI) 17(12), 1140–1153 (1995)

    Article  Google Scholar 

  47. Rosin, P.L.: Techniques for Assessing Polygonal Approximation of Curves. Pattern Analysis and Machine Intelligence (PAMI) 19(6), 659–666 (1997)

    Article  Google Scholar 

  48. Song, J., Su, F., Tai, C., Cai, S.: An Object-Oriented Progressive-Simplification based Vectorisation System for Engineering Drawings: Model, Algorithm and Performance. Pattern Analysis and Machine Intelligence (PAMI) 24(8), 1048–1060 (2002)

    Article  Google Scholar 

  49. Song, J., Cai, M., Lyu, M.R., Cai, S.: Graphics Recognition from Binary Images: One Step or Two Steps. In: International Conference on Pattern Recognition, ICPR (2002)

    Google Scholar 

  50. Song, J., Cai, M., Lyu, M.R., Cai, S.: A New Approach for Line Recognition in Large-Size Images Using Hough Transform. In: International Conference on Pattern Recognition, ICPR (2002)

    Google Scholar 

  51. Song, J., Lyu, M.R., Cai, M., Cai, S.: Graphic Object Recognition from Binary Images: a Survey and an Integrated Paradigm. Transactions on Systems, Man and Cybernetics, part C: Applications and Reviews (TSMCC) (under review)

    Google Scholar 

  52. Su, Y.M., Wang, J.F.: A Learning Process to the Identification of Feature Points on Chinese Characters. In: International Conference on Pattern Recognition, ICPR (2002)

    Google Scholar 

  53. Tombre, K.: Structural and Syntactic Methods in Line Drawing Analysis: To Which Extent do they Work? In: Perner, P., Rosenfeld, A., Wang, P. (eds.) SSPR 1996. LNCS, vol. 1121. Springer, Heidelberg (1996)

    Google Scholar 

  54. Tombre, K., Ah-Soon, C., Dosch, P., Masini, G., Tabbone, S.: Stable and Robust Vectorization: How to Make the Right Choices. In: Chhabra, A.K., Dori, D. (eds.) GREC 1999. LNCS, vol. 1941, p. 3. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  55. Trier, O.D., Jain, A.K., Taxt, T.: Features Extraction Methods for Character Recognition –A Survey. Pattern Recognition (PR) 29(4), 641–662 (1996)

    Article  Google Scholar 

  56. Turner, M.J., Wiseman, N.E.: Efficient Lossless Image Contour Coding. Computer Graphics Forum 15(2), 107–118 (1996)

    Article  Google Scholar 

  57. Vaxivière, P., Tombre, K.: Subsampling: A Structural Approach to Technical Document Vectorisation. In: Syntactic and Structural Pattern Recognition, SSPR (1995)

    Google Scholar 

  58. Vinciarelli, A.: A Survey on Off-Line Cursive Word Recognition. Pattern Recognition (PR) 35(7), 1443–1446 (2002)

    Google Scholar 

  59. Weindorf, M.: Structure Based Interpretation of Unstructured Vector Maps. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, p. 190. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  60. Xue, H.: Building Skeletal Graphs for Structural Feature Extraction on Handwriting Images. In: International Conference on Document Analysis And Recognition, ICDAR (2001)

    Google Scholar 

  61. Yoon, S., Kim, G., Choi, Y., Lee, Y.: New Paradigm for Segmentation and Recognition. In: Graphics Recognition, GREC (2001)

    Google Scholar 

  62. Zou, J.J., Yan, H.: Vectorization of Cartoon Drawings. In: Visual Information (2000)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Laboratory PSI, University of Rouen, 76 821, Mont Saint Aignan, France

    Mathieu Delalandre & Eric Trupin

  2. Laboratory L3I, University of La Rochelle, 17042, La Rochelle, France

    Jean-Marc Ogier

Authors
  1. Mathieu Delalandre
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  2. Eric Trupin
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  3. Jean-Marc Ogier
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Editor information

Editors and Affiliations

  1. Computer Vision Center, Universitat Autònoma de Barcelona, Bellaterra, 08193, (Barcelona), Spain

    Josep Lladós

  2. Departmen Computer Science and Engineering, Chung-Ang University, 221 Heuksukdong, Dongjakku, Seoul, Korea

    Young-Bin Kwon

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© 2004 Springer-Verlag Berlin Heidelberg

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Delalandre, M., Trupin, E., Ogier, JM. (2004). Local Structural Analysis: A Primer. In: Lladós, J., Kwon, YB. (eds) Graphics Recognition. Recent Advances and Perspectives. GREC 2003. Lecture Notes in Computer Science, vol 3088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25977-0_21

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  • DOI: https://doi.org/10.1007/978-3-540-25977-0_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22478-5

  • Online ISBN: 978-3-540-25977-0

  • eBook Packages: Springer Book Archive

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