• Abhishek Mehta
• Ashish Chaturvedi

Hindi is that the most usually auditory communication in India, with in more than three hundred million speakers. As there's no division between the characters of writings written in Hindi as there's in English, the Optical Character Recognition (OCR) frameworks created for the Hindi language convey a poor recognition rate. During this paper we have a tendency to propose AN OCR for written Hindi content in Devanagari script content, utilizing Artificial Neural Network (ANN), that improves its productivity. one in every of the numerous functions behind the poor recognition rate is mistake in character division. The closeness of contacting characters within the examined records more entangles the division procedure, creating an interesting issue once designing a compelling character division methodology. Pre-processing, character division, embrace extraction; lastly, grouping and recognition area unit the important advances that area unit pursued by a general OCR. The pre-processing tasks thought of inside the paper conversion of gray scaled footage to binary footage, image rectification, and segmentation of the document´s matter contents into paragraphs, lines, words, thus at the extent of basic symbols. the basic symbols, obtained as a result of the essential unit from the segmentation methodology, recognized by the neural classifier. Neural Network is one in every of the foremost wide used and common techniques for character recognition downside. This paper discusses the classification and recognition of written Hindi Vowels and Consonants mistreatment Artificial Neural Networks. The vowels and consonants in Hindi characters are often divided in to sub teams supported bound vital characteristics for every cluster, a separate network is meant and trained to acknowledge the characters that belong to it cluster.

Pattern Recognition, Character Recognition, Artificial Neural Network, Feature Extraction, Thinning, OCR, Pre-Processing, Segmentation, Feature Vector, Classification, Noise Removal.

"Extraction and Recognition of Handwritten Hindi and Gujarati Character Using Artificial Neural- network Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.74-80, May 2019, Available :http://www.jetir.org/papers/JETIRCY06012.pdf

"Extraction and Recognition of Handwritten Hindi and Gujarati Character Using Artificial Neural- network Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp74-80, May 2019, Available at : http://www.jetir.org/papers/JETIRCY06012.pdf