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

dc.contributor.authorPirsiavash, Hamed
dc.contributor.authorMehran, Ramin
dc.contributor.authorRazzazi, Farbod
dc.date.accessioned2019-07-03T17:19:44Z
dc.date.available2019-07-03T17:19:44Z
dc.date.issued2005
dc.description.abstractOptical 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_US
dc.description.sponsorshipThe authors would like to thank and acknowledge the Paya Soft co. that sponsored this research.en_US
dc.description.urihttps://link.springer.com/chapter/10.1007/11578079_63en_US
dc.format.extent11 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/m2qww4-t8s2
dc.identifier.citationPirsiavash 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, Heidelbergen_US
dc.identifier.urihttps://doi.org/10.1007/11578079_63
dc.identifier.urihttp://hdl.handle.net/11603/14339
dc.language.isoen_USen_US
dc.publisherSpringer, Berlin, Heidelbergen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis 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.subjectSupport Vector Machineen_US
dc.subjectNatural Language Processingen_US
dc.subjectFuzzy Inference Systemen_US
dc.subjectSupport Vector Machine Classifieren_US
dc.subjectMulti Layer Perceptronsen_US
dc.titleA Robust Free Size OCR for Omni-font Persian/Arabic Printed Document using Combined MLP/SVMen_US
dc.typeTexten_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
20880778.pdf
Size:
192.28 KB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.56 KB
Format:
Item-specific license agreed upon to submission
Description: