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Hidden Markov Models For Two-Dimensional Data

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Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 226))

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

  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. 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 

  4. 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 

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

  6. 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, vol. 6113, pp. 523–530. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  7. 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 

  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. Samaria, F., Young, S.: HMM-based Architecture for Face Identification. Image and Vision Computing 12(8), 537–583 (1994)

    Article  Google Scholar 

  10. 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 

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

    Article  MathSciNet  MATH  Google Scholar 

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Authors and Affiliations

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

    Janusz Bobulski

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  1. Janusz Bobulski
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Correspondence to Janusz Bobulski .

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Editors and Affiliations

  1. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Robert Burduk

  2. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Konrad Jackowski

  3. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Marek Kurzynski

  4. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Michał Wozniak

  5. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St, Wroclaw, 50-370, Poland

    Andrzej Zolnierek

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Bobulski, J. (2013). Hidden Markov Models For Two-Dimensional Data. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_14

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  • DOI: https://doi.org/10.1007/978-3-319-00969-8_14

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00968-1

  • Online ISBN: 978-3-319-00969-8

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