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An Error-Correction Graph Grammar to Recognize Texture Symbols

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Graphics Recognition Algorithms and Applications (GREC 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2390))

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Abstract

This paper presents an algorithm for recognizing symbols with textured elements in a graphical document. A region adjacency graph represents the document. The texture symbols are modeled by a graph grammar. An inference algorithm is applied to learn such grammar from an instance of the texture. For recognition, a parsing process is applied. Since documents present distortions, error-correcting rules are added to the grammar.

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References

  1. S. Ablameyko. An introduction to interpretation of graphic images, volume TT27 of Tutorial Texts in Optical Engineering, chapter Recognition of cartographic objects, pp. 92–123. SPIE The international society for Optical Engineering, 1997.

    Google Scholar 

  2. D. Antoine, S. Collin, K. Tombre. Analysis of technical documents: The REDRAW system. In H. Baird, H. Bunke, K. Yamamoto, eds.: Structured document image analysis. Springer Verlag (1992) 385–402.

    Google Scholar 

  3. L. Boatto, et al. An interpretation system for land register maps. Computer, 25:25–33, 1992.

    Article  Google Scholar 

  4. H. Bunke. Attributed Programmed Graph Grammars and Their Application to Schematic Diagram Interpretation. IEEE Transactions on PAMI, 4(6):574–582, November 1992.

    Google Scholar 

  5. D. Dori. A syntactic/geometric approach to recognition of dimensions in engineering machine drawings. Computer Vision, Graphics and Image Processing, 1989.

    Google Scholar 

  6. H. Fahmy and D. Blostein. A graph grammar programing style for recognition of music notation. Machine Vision and Aplications 6:83–99, 1993.

    Article  Google Scholar 

  7. L. G. C. Hamey. Computer Perception of Repetitive Textures. PhD thesis, Computer Science Department, Carnegie Mellon University, Pittsburg, 1988.

    Google Scholar 

  8. T. Kasvand. Linear textures in line drawings. In Proc. in the 8th Int. Conf. on Pattern Recognition, 1986.

    Google Scholar 

  9. A. Kosmala, S. Lavirotte, L. Pottier, and G. Rigoll. On-Line Handwritten Formula Recognition using Hidden Markov Models and Context Dependent Graph Grammars. In Proc. of 5th Int. Conf. on Document Analysis and Recognition, 1999.

    Google Scholar 

  10. J. Lladós, G. Sánchez and E. Martí. A string-based method to recognize symbols and structural textures in architectural plans. Graphics Recognition, Algorithms and Systems. K. Tombre and A. K. Chhabra (eds). Lecture Notes in Computer Science, Springer-Verlag, 1389:91–103, 1998.

    Google Scholar 

  11. J. Lladós, E. Martí and J. J. Villanueva. Symbol Recognition by Error-Tolerant Subgraph Matching between Region Adjacency Graphs. IEEE Transactions on PAMI. 23(10):1137–1143, October, 2001.

    Google Scholar 

  12. S. Y. Lu and K. S. Fu. A syntactic approach to texture analysis. Computer Graphics and Image Processing, 7:303–330, 1978.

    Article  Google Scholar 

  13. T. Matsuyama, K. Saburi, and M. Nagao. A structural analyzer for regularly arranged textures. Computer Graphics and Image Processing, 18, 1982.

    Google Scholar 

  14. W. Min, Z. Tang, and L. Tang. Using web grammar to recognize dimensions in engineering drawings. Pattern Recognition, 26(9):1407–1916, 1993.

    Article  Google Scholar 

  15. J. Rekers and A. Schürr. Defining and Parsing Visual Languages with Layered Graph Grammars. Journal of Visual Languages and Computing, 8(1):27–55, London: Academic Press (1997).

    Google Scholar 

  16. G. Rozenberg. Handbook of Graph Grammars and Computing by Graph Transformation. Vol. I, Foundations, World Scientific, 1997.

    Google Scholar 

  17. G. Sánchez, J. Lladós and K. Tombre. A Mean String Algorithm to Compute the Average Among a Set of 2D Shapes. Pattern Recognition Letters. 23(1–3):203–213, January 2002.

    Google Scholar 

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Sánchez, G., Lladós, J., Tombre, K. (2002). An Error-Correction Graph Grammar to Recognize Texture Symbols. In: Blostein, D., Kwon, YB. (eds) Graphics Recognition Algorithms and Applications. GREC 2001. Lecture Notes in Computer Science, vol 2390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45868-9_10

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  • DOI: https://doi.org/10.1007/3-540-45868-9_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44066-6

  • Online ISBN: 978-3-540-45868-5

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