EM Training of Hidden Markov Models for Shape Recognition Using Cyclic Strings

  • Vicente Palazón-González
  • Andrés Marzal
  • Juan M. Vilar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8228)


Shape descriptions and the corresponding matching techniques must be robust to noise and invariant to transformations for their use in recognition tasks. Most transformations are relatively easy to handle when contours are represented by strings. However, starting point invariance is difficult to achieve. One interesting possibility is the use of cyclic strings, which are strings with no starting and final points. Here we present the use of Hidden Markov Models for modelling cyclic strings and their training using Expectation Maximization. Experimental results show that our proposal outperforms other methods in the literature.


hidden markov models cyclic strings shape recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Vicente Palazón-González
    • 1
  • Andrés Marzal
    • 1
  • Juan M. Vilar
    • 1
  1. 1.Dept. Llenguatges i Sistemes Informàtics and Institute of New Imaging TechnologiesUniversitat Jaume I de Castelló.Spain

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