@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}, }