Multifont Arabic character recognition using Hough transform and hidden Markov models Export

@proceedings{citeulike:1705058, abstract = {Optical characters recognition (OCR) has been an active subject of research since the early days of Computers. Despite the age of the subject, it remains one of the most challenging and exciting areas of research in computer science. In recent years it has grown into a mature discipline, producing a huge body of work. Arabic character recognition has been one of the last major languages to receive attention. This is due, in part, to the cursive nature of the task since even printed Arabic characters are in cursive form. This paper describes the performance of combining Hough transform and hidden Markov models in a multifont Arabic OCR system. Experimental tests have been carried out on a set of 85,000 samples of characters corresponding to 5 different fonts from the most commonly used in Arabic writing. Some promising experimental results are reported.}, author = {Amor, N. B. and Amara, N. E. B.}, booktitle = {Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on}, citeulike-article-id = {1705058}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1521303}, journal = {Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on}, keywords = {arabic, arabic\_ocr, for\_gabe, hmms, ocr}, pages = {285--288}, posted-at = {2007-09-28 14:45:59}, priority = {0}, title = {Multifont Arabic character recognition using Hough transform and hidden Markov models}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1521303}, year = {2005} }

TY - CONF ID - citeulike:1705058 L3 - citeulike-article-id:1705058 N2 - Optical characters recognition (OCR) has been an active subject of research since the early days of Computers. Despite the age of the subject, it remains one of the most challenging and exciting areas of research in computer science. In recent years it has grown into a mature discipline, producing a huge body of work. Arabic character recognition has been one of the last major languages to receive attention. This is due, in part, to the cursive nature of the task since even printed Arabic characters are in cursive form. This paper describes the performance of combining Hough transform and hidden Markov models in a multifont Arabic OCR system. Experimental tests have been carried out on a set of 85,000 samples of characters corresponding to 5 different fonts from the most commonly used in Arabic writing. Some promising experimental results are reported. JF - Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on EP - 288 TI - Multifont Arabic character recognition using Hough transform and hidden Markov models T2 - Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on SP - 285 KW - arabic KW - arabic_ocr KW - for_gabe KW - hmms KW - ocr AU - Amor, NB AU - Amara, NEB PY - 2005/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1521303 ER -