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Parallel Computing Scheme for Graph Grammar-Based Syntactic Pattern Recognition

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Parallel Processing and Applied Mathematics (PPAM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6067))

Abstract

Real-time syntactic pattern recogniton imposes strict computing time constraints on new techniques developed. Recently, a method for an analysis of hand postures of the Polish Sign Language based on the ETPL(k) graph grammars (Flasiński: Patt. Recogn. 26 (1993), 1-16; Theor. Comp. Sci. 201 (1998), 189-231) has been constructed. In order to make a system implemented more feasible for the users, a research into parallelization of a pattern recognition process has been led. Possible techniques of tasks distribution have been tested. It has allowed us to define an optimum strategy of parallelization. The results are presented in the paper.

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References

  1. Chiang, Y., Fu, K.S.: Parallel parsing algorithms and VLSI implementation for syntactic pattern recognition. IEEE Trans. Pattern Anal. Machine Intell. PAMI-6, 302–313 (1984)

    Article  Google Scholar 

  2. Davis, L.S., Rosenfeld, A., Inoue, K., Nivat, M., Wang, P.S.P. (eds.): Parallel Image Analysis: Theory and Applications. World Scientific, Singapore (1995)

    MATH  Google Scholar 

  3. Flasiński, M.: Parsing of edNLC-graph grammars for scene analysis. Pattern Recognition 21, 623–629 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  4. Flasiński, M., Kotulski, L.: On the use of graph grammars for the control of a distributed software allocation. The Computer Journal 35, A165–A175 (1992)

    Google Scholar 

  5. Flasiński, M.: On the parsing of deterministic graph languages for syntactic pattern recognition. Pattern Recognition 26, 1–16 (1993)

    Article  MathSciNet  Google Scholar 

  6. Flasiński, M.: Use of graph grammars for the description of mechanical parts. Computer Aided Design 27, 403–433 (1995)

    Article  MATH  Google Scholar 

  7. Flasiński, M.: Power properties of NLC graph grammars with a polynomial membership problem. Theoretical Computer Science 201, 189–231 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  8. Flasiński, M.: Automata-based multi-agent model as a tool for constructing real-time intelligent control systems. In: Dunin-Keplicz, B., Nawarecki, E. (eds.) CEEMAS 2001. LNCS (LNAI), vol. 2296, pp. 103–110. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  9. Flasiński, M.: Inference of parsable graph grammars for syntactic pattern recognition. Fundamenta Informaticae 80, 379–413 (2007)

    MATH  MathSciNet  Google Scholar 

  10. Flasiński, M., Jurek, J., Myśliński, S.: Multi-agent system for recognition of hand postures. In: Allen, G., et al. (eds.) ICCS 2009, Part II. LNCS, vol. 5545, pp. 815–824. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  11. Guerra, C.: 2D object recognition on a reconfigurable mesh. Pattern Recognition 31, 83–88 (1998)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  13. Klaiber, A., Gokhale, M.: Parallel evaluation of attributed grammars. IEEE Trans. Parall. Distr. Syst. 3, 206–220 (1992)

    Article  Google Scholar 

  14. Lee, S.S., Tanaka, H.T.: Parallel image segmentation with adaptive mesh. In: Proc. 15th Int. Conf. Patt. Recogn., Barcelona, Spain, September 2000, vol. 1, pp. 635–639 (2000)

    Google Scholar 

  15. Miguet, S., Montanvert, A., Wang, P.S.P. (eds.): Parallel Image Analysis. World Scientific, Singapore (1998)

    MATH  Google Scholar 

  16. Myśliński, S.: On the generation of graph representation of hand postures for syntactic pattern recognition. Journal of Applied Computer Science 17 (2009)

    Google Scholar 

  17. Pavlatos, C., Panagopoulos, I., Papakonstantinou, G.: A programmable pipelined coprocessor for parsing applications. In: Proc. Workshop on Application Specific Processors, Stockholm, September 2004, pp. 84–91 (2004)

    Google Scholar 

  18. Rabah, H., Mathias, H., Weber, S., Mozef, E., Tanougast, C.: Linear array processors with multiple access modes memory for real-time image processing. Real Time Imaging 9, 205–213 (2003)

    Article  Google Scholar 

  19. Ranganathan, N. (ed.): VLSI and Parallel Computing for Pattern Recognition and Artificial Intelligence. World Scientific, Singapore (1995)

    MATH  Google Scholar 

  20. Sideri, M., Efremidis, S., Papakonstantinou, G.: Semantically driven parsing of CFG. The Computer Journal 32, 91–98 (1994)

    Article  Google Scholar 

  21. Tokuda, T., Watanabe, Y.: An attribute evaluation of context-free languages. Information Processing Letter 57, 91–98 (1994)

    Article  Google Scholar 

  22. Weschler, H.: An overview of parallel hardware architectures for computer vision. Int. J. Patt. Recogn. Artif. Intell. 6, 629–649 (1992)

    Article  Google Scholar 

  23. Wu, A.Y., Bhaskar, S.K., Rosenfeld, A.: Parallel processing of region boundaries. Pattern Recognition 22, 165–172 (1989)

    Article  Google Scholar 

  24. Wu, A.Y., Rosenfeld, A.: Parallel processing of encoded bit strings. Pattern Recognition 21, 559–565 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  25. Yalamanchili, S., Aggarwal, J.K.: Analysis of a model for parallel image processing. Pattern Recognition 18, 1–16 (1985)

    Article  Google Scholar 

  26. Zhang, D., Pal, S.K. (eds.): Neural Networks and Systolic Array Design. Series in Machine Perception and Artificial Intelligence, vol. 49. World Scientific, Singapore (2002)

    MATH  Google Scholar 

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Flasiński, M., Jurek, J., Myśliński, S. (2010). Parallel Computing Scheme for Graph Grammar-Based Syntactic Pattern Recognition. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2009. Lecture Notes in Computer Science, vol 6067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14390-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-14390-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14389-2

  • Online ISBN: 978-3-642-14390-8

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