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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2013: Artificial Intelligence and Soft Computing pp 515–523Cite as

Two-Dimensional Hidden Markov Models for Pattern Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7894))

Abstract

Hidden Markov models are well-known methods for image processing. They are used in many areas where 1D data are processed. In the case of 2D data, there appear some problems with application HMM. There are some solutions, but they convert input observation from 2D to 1D, or create parallel pseudo 2D HMM, which is set of 1D HMMs in fact. This paper describes authentic 2D HMM with two-dimensional input data, and its application for pattern recognition in image processing.

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References

  1. Kompanets, L., Kubanek, M., Rydzek, S.: Czestochowa-Faces and Biometrics of Asymmetrical Face. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 742–747. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  2. Eickeler, S., Müller, S., Rigoll, G.: High Performance Face Recognition Using Pseudo 2-D Hidden Markov Models. In: European Control Conference (1999), http://citeseer.ist.psu.edu

  3. Vitoantonio Bevilacqua, V., Cariello, L., Carro, G., Daleno, D., Mastronardi, G.: A face recognition system based on Pseudo 2D HMM applied to neural network coefficients. Soft Comput. 12(7), 615–621 (2008)

    Article  Google Scholar 

  4. Kubanek, M.: Automatic Methods for Determining the Characteristic Points in Face Image. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part I. LNCS (LNAI), vol. 6113, pp. 523–530. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  5. Li, J., Najmi, A., Gray, R.M.: Image classification by a two dimensional Hidden Markov model. IEEE Transactions on Signal Processing 48, 517–533 (2000)

    Article  Google Scholar 

  6. Joshi, D., Li, J., Wang, J.Z.: A computationally Efficient Approach to the estimation of two- and three-dimensional hidden Markov models. IEEE Transactions on Image Processing 15(7), 1871–1886 (2006)

    Article  MathSciNet  Google Scholar 

  7. Li, Y.: An analytic solution for estimating two-dimensional hidden Markov models. Applied Mathematics and Computation 185, 810–822 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  8. Rabiner, L.R.: A tutorial on hidden Markov models and selected application in speech recognition. Proc. IEEE 77, 257–285 (1989)

    Article  Google Scholar 

  9. Kanungo, T.: Hidden Markov Model Tutorial (1999), http://www.kanungo.com/software/hmmtut.pdf

  10. Forney, G.D.: The Viterbi Algorithm. Proc. IEEE 61(3), 268–278 (1973)

    Article  MathSciNet  Google Scholar 

  11. Geusebroek, J.M., Burghouts, G.J., Smeulders, A.W.M.: The Amsterdam library of object images. Int. J. Comput. Vision 61(1), 103–112 (2005)

    Article  Google Scholar 

  12. Amsterdam Library of Object Images, http://www.science.uva.nl/~aloi

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Author information

Authors and Affiliations

  1. Institute of Computer and Information Science, Czestochowa University of Technology, Dabrowskiego Street 73, 42-200, Czestochowa, Poland

    Janusz Bobulski & Lukasz Adrjanowicz

Authors
  1. Janusz Bobulski
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  2. Lukasz Adrjanowicz
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Michiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2013 Springer-Verlag Berlin Heidelberg

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Bobulski, J., Adrjanowicz, L. (2013). Two-Dimensional Hidden Markov Models for Pattern Recognition. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_46

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  • DOI: https://doi.org/10.1007/978-3-642-38658-9_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38657-2

  • Online ISBN: 978-3-642-38658-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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