@article{(Open Science Index):https://publications.waset.org/pdf/9003,
	  title     = {Recognition-based Segmentation in Persian Character Recognition},
	  author    = {Mohsen Zand and  Ahmadreza Naghsh Nilchi and  S. Amirhassan Monadjemi},
	  country	= {},
	  institution	= {},
	  abstract     = {Optical character recognition of cursive scripts
presents a number of challenging problems in both segmentation and
recognition processes in different languages, including Persian. In
order to overcome these problems, we use a newly developed Persian
word segmentation method and a recognition-based segmentation
technique to overcome its segmentation problems. This method is
robust as well as flexible. It also increases the system-s tolerances to
font variations. The implementation results of this method on a
comprehensive database show a high degree of accuracy which meets
the requirements for commercial use. Extended with a suitable pre
and post-processing, the method offers a simple and fast framework
to develop a full OCR system.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {2},
	  year      = {2008},
	  pages     = {311 - 315},
	  ee        = {https://publications.waset.org/pdf/9003},
	  url   	= {https://publications.waset.org/vol/14},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 14, 2008},
	}