{"title":"Multi-Font Farsi\/Arabic Isolated Character Recognition Using Chain Codes","authors":"H. Izakian, S. A. Monadjemi, B. Tork Ladani, K. Zamanifar","volume":19,"journal":"International Journal of Computer and Information Engineering","pagesStart":2315,"pagesEnd":2319,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/301","abstract":"Nowadays, OCR systems have got several\napplications and are increasingly employed in daily life. Much\nresearch has been done regarding the identification of Latin,\nJapanese, and Chinese characters. However, very little investigation\nhas been performed regarding Farsi\/Arabic characters recognition.\nProbably the reason is difficulty and complexity of those characters\nidentification compared to the others and limitation of IT activities in\nFarsi and Arabic speaking countries. In this paper, a technique has\nbeen employed to identify isolated Farsi\/Arabic characters. A chain\ncode based algorithm along with other significant peculiarities such\nas number and location of dots and auxiliary parts, and the number of\nholes existing in the isolated character has been used in this study to\nidentify Farsi\/Arabic characters. Experimental results show the\nrelatively high accuracy of the method developed when it is tested on\nseveral standard Farsi fonts.","references":"[1] M. M. Altuwaijri and M. A.Bayoumi, \"Arabic text recognition using\nneural networks\", IEEE International Symposium on Circuits and\nSystems, pp;415-418, 1994.\n[2] B.M.F.Bushofa and M.Spann, \"Segmentation and recognition of Arabic\ncharacters by structural classification\",Image and Vision Computing, ,\n15,pp:167-179, 1997.\n[3] B. Al-Badr and S. A. Mahmoud, \"Survey and bibliography of Arabic\noptical text recognition\", Signal Processing, 41, pp:49-77, 1995.\n[4] L. Zheng, Abbas H. 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