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A Novel Approach of Multi-string Parsing for Syntactic Pattern Recognition

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Progress on Pattern Classification, Image Processing and Communications (CORES 2023, IP&C 2023)

Abstract

A novel approach to syntactic pattern recognition based on multi-string parsing is introduced in the paper. A methodological motivation of the research, which has resulted from application-oriented requirements, is presented. Formal foundations, an architectural model and a generic recognition algorithm of the approach are introduced. The approach allows one to recognize complex objects which should be represented by a series of images instead of one image. The series of images is represented with a sequence of aspectual patterns which are treated as a holistic aspect-integrated description of a recognized object.

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Notes

  1. 1.

    The “optimum” image would mean the image with the “optimum” value of the binarization threshold. Simply, there is no such an “optimum” threshold in this case.

References

  1. Asveld, P.R.J.: Fuzzy context-free languages (Part I and II). Theor. Comput. Sci. 347, 167–213 (2005)

    Article  MATH  Google Scholar 

  2. Bunke, H., Sanfeliu, A. (eds.): Syntactic and Structural Pattern Recognition - Theory and Applications. World Scientific, Singapore (1990)

    MATH  Google Scholar 

  3. Chan, K.F., Yeung, D.Y.: Error detection, error correction and performance evaluation in on-line mathematical expression recognition. Pattern Recogn. 34, 1671–1684 (2001)

    Article  MATH  Google Scholar 

  4. Cruz-Alcazar, P.P., Vidal, E.: Two grammatical inference applications in music processing. Appl. Artif. Intell. 22, 53–76 (2008)

    Article  Google Scholar 

  5. Ferreira, M., Santos, C., Monteiro, J.: Cork parquet quality control vision system based on texture segmentation and fuzzy grammar. IEEE Trans. Ind. Electron. 56, 756–765 (2009)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  7. Flasiński, M., Jurek, J.: Dynamically programmed automata for quasi contexts sensitive languages as a tool for inference support in pattern recognition-based real-time control expert systems. Pattern Recogn. 32, 671–690 (1999)

    Article  Google Scholar 

  8. Flasiński, M., Reroń, E., Jurek, J., Wójtowicz, P., Atłasiewicz, K.: On the construction of the syntactic pattern recognition-based expert system for Auditory Brainstem Response analysis. In: Kurzyński, M., Puchała, E., Woźniak, M., Żołnierek, A. (eds.) CORES 2005. Advances in Soft Computing, vol. 30, pp. 503–510, Springer, Heidelberg (2005). https://doi.org/10.1007/3-540-32390-2_59

  9. Flasiński, M., Jurek, J.: On the analysis of fuzzy string patterns with the help of extended and stochastic GDPLL(k) grammars. Fundamenta Informaticae 71, 1–14 (2006)

    MathSciNet  MATH  Google Scholar 

  10. Flasiński, M.: Introduction to Artificial Intelligence. Springer, Switzerland (2016)

    Book  MATH  Google Scholar 

  11. Flasiński, M.: Syntactic Pattern Recognition. World Scientific, Singapore (2019)

    Book  MATH  Google Scholar 

  12. Flasiński, M., Jurek, J., Peszek, T.: On the learning of vague languages for syntactic pattern recognition. Pattern Anal. Appl. (2022). https://doi.org/10.1007/s10044-022-01120-0

  13. Fu, K.S.: Syntactic Pattern Recognition and Applications. Prentice Hall, Upper Saddle River (1982)

    MATH  Google Scholar 

  14. Gonzales, R.C., Thomason, M.G.: Syntactic Pattern Recognition: An Introduction. Addison-Wesley, Boston (1978)

    MATH  Google Scholar 

  15. Huang, K.Y.: Syntactic Pattern Recognition for Seismic Oil Exploration. World Scientific, Singapore (2002)

    Book  Google Scholar 

  16. Jurek, J.: On the linear computational complexity of the parser for quasi context sensitive languages. Pattern Recogn. Lett. 21, 179–187 (2000)

    Article  Google Scholar 

  17. Jurek, J.: Recent developments of the syntactic pattern recognition model based on quasi-context sensitive languages. Pattern Recogn. Lett. 26, 1011–1018 (2005)

    Article  Google Scholar 

  18. Jurek, J., Wójtowicz, W., Wójtowicz, A.: Syntactic pattern recognition-based diagnostics of fetal palates. Pattern Recogn. Lett. 133, 144–150 (2020)

    Article  Google Scholar 

  19. Lewis, P.M., II., Stearns, R.E.: Syntax-directed transduction. J. ACM 15, 465–488 (1968)

    Article  MATH  Google Scholar 

  20. Lopez, D., Sempere, J.M., Garcia, P.: Error correcting analysis for tree languages. Int. J. Pattern Recogn. Artif. Intell. 14, 357–368 (2000)

    Article  Google Scholar 

  21. Mordeson, J.N., Malik, D.S.: Fuzzy Automata and Languages: Theory and Applications. Chapman and Hall - CRC, Boca Raton (2002)

    Book  MATH  Google Scholar 

  22. Rosenkrantz, D.J.: Programmed grammars and classes of formal languages. J. ACM 16, 107–131 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  23. Rosenkrantz, D.J., Stearns, R.E.: Properties of deterministic top-down grammars. Inf. Control 17, 226–256 (1970)

    Article  MathSciNet  MATH  Google Scholar 

  24. Thomason, M.G.: Generating functions for stochastic context-free grammars. Int. J. Pattern Recogn. Artif. Intell. 4, 553–572 (1990)

    Article  Google Scholar 

  25. Vidal, E., Thollard, F., Higuera, C., Casacuberta, F., Carrasco, R.: Probabilistic finite-state machines (Part I and II). IEEE Trans. Pattern Anal. Mach. Intell. 27, 1013–1039 (2005)

    Article  Google Scholar 

  26. Wójtowicz, A., Wójtowicz, W., Jurek, J., Huras, H.: Evaluation of the fetal palate at 11 to 13 (+6) weeks of gestation based on an analysis of static ultrasound images using modern IT techniques. Prenatal Diagn. 38, 414–421 (2018)

    Article  Google Scholar 

  27. Zhu, S.C., Mumford, D.: A stochastic grammar of images. Found. Trends Comput. Graph. Vision 2, 259–362 (2007)

    Article  MATH  Google Scholar 

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Correspondence to Mariusz Flasiński .

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Flasiński, M., Jurek, J. (2023). A Novel Approach of Multi-string Parsing for Syntactic Pattern Recognition. In: Burduk, R., Choraś, M., Kozik, R., Ksieniewicz, P., Marciniak, T., Trajdos, P. (eds) Progress on Pattern Classification, Image Processing and Communications. CORES IP&C 2023 2023. Lecture Notes in Networks and Systems, vol 766. Springer, Cham. https://doi.org/10.1007/978-3-031-41630-9_1

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