Pirsiavash, HamedMehran, RaminRazzazi, Farbod2019-07-032019-07-032005Pirsiavash 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, Heidelberghttps://doi.org/10.1007/11578079_63http://hdl.handle.net/11603/14339Optical 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.11 pagesen-USThis 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.Support Vector MachineNatural Language ProcessingFuzzy Inference SystemSupport Vector Machine ClassifierMulti Layer PerceptronsText