Word Recognition by MLP-based Character Spotting and Dynamic Programming

  • F. Camastra
  • E. Cepollina
  • A. M. Colla
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)


This paper describes a method for handprinted word recognition, with the following characteristics: traditional pre-processing (relevant to single characters, obtained by word segmentation) is replaced by pre-processing based on piecewise normalization applied at whole words; feature extraction and character classification by MLP are performed in a sliding window fashion; the output string is matched with an ASCII word vocabulary by Dynamic Programming with the Levenshtein distance; a list of word candidates is issued. Afterwards, when the language is formally known, an appropriate parser can be applied to full Sentence Recognition. Tests on a medium size vocabulary show extremely promising results.




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Copyright information

© Springer-Verlag London Limited 1998

Authors and Affiliations

  • F. Camastra
    • 1
  • E. Cepollina
    • 2
  • A. M. Colla
    • 1
  1. 1.Elsag Bailey - Un’Azienda Finmeccanica S.p.AGenovaItaly
  2. 2.Dip. Informatica e Scienze dell’InformazioneUniversità di GenovaGenovaItaly

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