Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review

Authors

  • Mimansha Agrawal
  • Bhanu Chauhan
  • Tanisha Agrawal

DOI:

https://doi.org/10.46243/jst.2022.v7.i01.pp01-16

Keywords:

Devanagari Script, Optical Character Recognition, Segmentation, Convolutional Neural Network (CNN), Support Vector Machine, Image Processing.

Abstract

Devanagari Character Recognition is a system in which handwritten Image is recognized and converted into a digital form. Devanagari handwritten character recognition system is based on Deep learning technique,

which manages the recognition of Devanagari script particularly Hindi. This recognition system mainly has five

stages i.e. Pre-processing, Segmentation, Feature Extraction, Prediction and Post processing. This paper has analyzed the approach for recognition of handwritten Devanagari characters. There are various approaches to solve this. Some of the methods along with their accuracy and techniques used are discussed here. Depending upon the dataset and accuracies of each character the techniques differs.

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Published

2022-01-06

How to Cite

Agrawal, M., Chauhan, B., & Agrawal, T. (2022). Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review. Journal of Science & Technology (JST), 7(1), 1–16. https://doi.org/10.46243/jst.2022.v7.i01.pp01-16

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