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

Thumbnail Image

Files

20880778.pdf (192.28 KB)

Links to Files

https://link.springer.com/chapter/10.1007/11578079_63

Permanent Link

https://doi.org/10.1007/11578079_63
 http://hdl.handle.net/11603/14339

Collections

UMBC Computer Science and Electrical Engineering Department
UMBC Faculty Collection

Author/Creator

Author/Creator ORCID

Date

2005

Type of Work

conference papers and proceedings preprints
Text

Department

Program

Citation of Original Publication

Pirsiavash H., Mehran R., Razzazi F. (2005) A Robust Free Size OCR for Omni-Font Persian/Arabic Printed Document Using Combined MLP/SVM. In: Sanfeliu A., Cortés M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Support Vector Machine
Natural Language Processing
Fuzzy Inference System
Support Vector Machine Classifier
Multi Layer Perceptrons

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.