@article{(Open Science Index):https://publications.waset.org/pdf/13307,
	  title     = {OCR for Script Identification of Hindi (Devnagari) Numerals using Error Diffusion Halftoning Algorithm with Neural Classifier },
	  author    = {Banashree N. P. and  Andhe Dharani and  R. Vasanta and  P. S. Satyanarayana},
	  country	= {},
	  institution	= {},
	  abstract     = {The applications on numbers are across-the-board that there is much scope for study. The chic of writing numbers is diverse and comes in a variety of form, size and fonts. Identification of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. There are plentiful approaches that deal with problem of detection of numerals/character depending on the sort of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent our work focused on a technique in feature extraction i.e. Local-based approach, a method using 16-segment display concept, which is extracted from halftoned images & Binary images of isolated numerals. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. Experimentation result shows that recognition rate of halftoned images is 98 % compared to binary images (95%).
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {2},
	  year      = {2007},
	  pages     = {307 - 311},
	  ee        = {https://publications.waset.org/pdf/13307},
	  url   	= {https://publications.waset.org/vol/2},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 2, 2007},
	}