A Comparative study on Handwritten Devanagari Character Recognition

EasyChair Preprint 3668

Abstract

Handwritten text recognition is a challenging task because of the vast changes in writing styles. In India, a massive number of people use Devanagari Script to write their documents, but due to large complexity, research work accomplished on this script is much lesser as com¬pared to English script. Hence, recognition of handwritten Devanagari Script is amongst the most demanding research areas in the field of image processing. Feature extraction and recognition are key steps of OCR which affects the accuracy of the character recognition system. This paper gives a comparative study on distinct techniques used for feature extraction and classification by the researchers over the last few years.

Keyphrases: ANN, CNN, Devanagari script, OCR, SVM, k-NN

@booklet{EasyChair:3668,
  author    = {Manoj Sonkusare and Roopam Gupta and Asmita Moghe},
  title     = {A Comparative study on Handwritten Devanagari Character Recognition},
  howpublished = {EasyChair Preprint 3668},
  year      = {EasyChair, 2020}}