A Robust Free Size OCR for Omni-Font Persian/Arabic Printed Document Using Combined MLP/SVM

  • Hamed Pirsiavash
  • Ramin Mehran
  • Farbod Razzazi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)

Abstract

Optical character recognition of cursive scripts present a number of challenging problems in both segmentation and recognition processes and this attracts many researches in the field of machine learning. This paper presents a novel approach based on a combination of MLP and SVM to design a trainable OCR for Persian/Arabic cursive documents. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use.

Keywords

Support Vector Machine Natural Language Processing Fuzzy Inference System Support Vector Machine Classifier Multi Layer Perceptrons 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hamed Pirsiavash
    • 1
    • 3
  • Ramin Mehran
    • 2
    • 3
  • Farbod Razzazi
    • 3
  1. 1.Department of Electrical EngineeringSharif University of TechnologyTehranIran
  2. 2.Department of Electrical EngineeringK.N.Toosi Univ. of Tech.TehranIran
  3. 3.Paya Soft co.TehranIran

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