Research Comparative Analysis of OCR Models for Urdu Language Characters Recognition

Authors

  • Muhammad Murad Institute of Computing, Alhamd Islamic University Quetta-Pakistan.
  • Muhammad Shahzad Institute of Computing, Alhamd Islamic University Quetta-Pakistan.
  • Naheeda Fareed Institute of Computing, Alhamd Islamic University Quetta-Pakistan.

DOI:

https://doi.org/10.5281/zenodo.14028816

Keywords:

Support Vector Machin (SVM), Convolutional Neural Network, Artificial Neural Network, Recurrent Neural Network (RNN), Optical Character Recognition, Transformer Model

Abstract

There have been many research works to digitalize Urdu Characters through machine learning algorithms. The algorithms that were already used for Urdu Optical Character Recognition [OCR] are Convolutional Neural Network [CNN], Recurrent Neural Network [RNN], and Transformer etc. There are also many machine learning algorithms that have not been used for Urdu OCR e.g Support Vector Machine, Graph Neural Network etc. This research paper proposes a comparative study between the performances of the already implemented Urdu OCR on some of following algorithms like Convolutional Neural Network/ Transformer Model it also proposed a new implemented Urdu OCR using on Support Vector Machine algorithm.

Downloads

Download data is not yet available.

Downloads

Published

2024-10-06

How to Cite

Muhammad Murad, Muhammad Shahzad, & Naheeda Fareed. (2024). Research Comparative Analysis of OCR Models for Urdu Language Characters Recognition. LC International Journal of STEM (ISSN: 2708-7123), 5(3), 55-63. https://doi.org/10.5281/zenodo.14028816