Syntactic Pattern Recognition by Error Correcting Analysis on Tree Automata

  • Damián López
  • Ignacio Piñaga
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1876)


Although the multidimensional primitives are more powerful than string primitives and there also exist some works concerning distance measure between multidimensional objects, there are no many applications of this kind of languages to syntactic pattern recognition tasks. In this work, multidimensional primitives are used for object modelling in a handwritten digit recognition task under a syntactic approach. Two well-known tree language inference algorithms are considered to build the models, using as error model an algorithm obtaining the editing distance between a tree automaton and a tree; the editing distance algorithm gives the measure needed to complete the classification. The experiments carried out show the good performance of the approach.


Syntactic pattern recognition editing distance tree automata error correcting parsing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Damián López
    • 1
  • Ignacio Piñaga
    • 1
  1. 1.Departamento de Sistemas Informáticos y ComputaciónUniversidad Politécnica de ValenciaValenciaSpain

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