![]() In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial Neural Network (ANN) which improves the efficiency. As there is no separation between the characters of the text written in Hindi similar to texts written in English, the Optical Character Recognition (OCR) systems developed for Hindi language carries a very poor recognition rate. "Hindi is the most spoken languages in India, with more than 300 million speaking it. The finding shows that the accuracy rate of character Segmentation is 89% and word segmentation is 91.70%. Objectives of this study are to find out the accuracy level of word and characters segmentation of Devanagari Script and then to analyze the Challenges faced during the process of word and character segmentation. Hence as effort have been generated to achieve a better rate of Segmentation in this Script. Challenging rate of OCR in Devanagari Script have not been solving in a better rate. The Devanagari Script makes a full set on many other scripts like Hindi, Konkani, Marathi, Nepali, Sanskrit, Bodo, Dogri and Maithili. A few works have been done in Devanagari Script. A large number of articles have been published in this area in various journals. These digitizing of document have various futuristic use such as record of old document could be kept in track, multiple data storage of handwritten or printed document, etc. The reason being that the OCR helps in digitizing the printed or handwritten document into computer readable format. ![]() ![]() In the subject Artificial Intelligence, OCR is of keen interest for the computer scientists and researchers. ![]()
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