A Robust Free Size OCR for Omni-font Persian/Arabic Printed Document using Combined MLP/SVM
| dc.contributor.author | Pirsiavash, Hamed | |
| dc.contributor.author | Mehran, Ramin | |
| dc.contributor.author | Razzazi, Farbod | |
| dc.date.accessioned | 2019-07-03T17:19:44Z | |
| dc.date.available | 2019-07-03T17:19:44Z | |
| dc.date.issued | 2005 | |
| dc.description.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. | en |
| dc.description.sponsorship | The authors would like to thank and acknowledge the Paya Soft co. that sponsored this research. | en |
| dc.description.uri | https://link.springer.com/chapter/10.1007/11578079_63 | en |
| dc.format.extent | 11 pages | en |
| dc.genre | conference papers and proceedings preprints | en |
| dc.identifier | doi:10.13016/m2qww4-t8s2 | |
| dc.identifier.citation | 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 | en |
| dc.identifier.uri | https://doi.org/10.1007/11578079_63 | |
| dc.identifier.uri | http://hdl.handle.net/11603/14339 | |
| dc.language.iso | en | en |
| dc.publisher | Springer, Berlin, Heidelberg | en |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.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. | |
| dc.subject | Support Vector Machine | en |
| dc.subject | Natural Language Processing | en |
| dc.subject | Fuzzy Inference System | en |
| dc.subject | Support Vector Machine Classifier | en |
| dc.subject | Multi Layer Perceptrons | en |
| dc.title | A Robust Free Size OCR for Omni-font Persian/Arabic Printed Document using Combined MLP/SVM | en |
| dc.type | Text | en |