A Survey on Handwritten Devanagari Character Recognition using Neural Network

Abstract

Handwritten character can be converted in to the digital information using handwritten character Recognition, which is the ability of a computer to receive and interpret handwritten input from documents. Handwritten Devanagari Characters are more complex for recognition due to presence of header line, conjunct characters and similarity in shapes of multiple characters. For Handwritten Devanagari Character recognition using neural network various approaches has been proposed. In general the process involves phases as: Scanning, Preprocessing, Feature Extraction and Recognition. Preprocessing includes noise reduction, binarization, normalization and thinning. Feature extraction includes extracting some useful information out of the thinned image in the form of a feature vector. Artificial neural network is used for classification. In this survey, comparative study of various approaches has been presented.

Authors and Affiliations

Prof. S. A. Dongare, Prof. N. J. Khapale, Prof. S. S. Dawange

Keywords

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  • EP ID EP23857
  • DOI http://doi.org/10.22214/ijraset.2017.4151
  • Views 284
  • Downloads 10

How To Cite

Prof. S. A. Dongare, Prof. N. J. Khapale, Prof. S. S. Dawange (2017). A Survey on Handwritten Devanagari Character Recognition using Neural Network. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(4), -. https://europub.co.uk./articles/-A-23857