A Robust Free Size OCR for Omni-font Persian/Arabic Printed Document using Combined MLP/SVM
Links to Fileshttps://link.springer.com/chapter/10.1007/11578079_63
MetadataShow full item record
Type of Work11 pages
conference papers and proceedings preprints
Citation of Original PublicationPirsiavash 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
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SubjectsSupport Vector Machine
Natural Language Processing
Fuzzy Inference System
Support Vector Machine Classifier
Multi Layer Perceptrons
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.