Research Article
Optical Character Recognition based on Genetic Algorithms and Machine Learning
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 172 - Issue 2 |
| Published: Aug 2017 |
| Authors: Arafat A. Muharram, Khaled M. G. Noaman, Ibrahim Abdulrab Ahmed, Jamil A. M. Saif |
10.5120/ijca2017915077
|
Arafat A. Muharram, Khaled M. G. Noaman, Ibrahim Abdulrab Ahmed, Jamil A. M. Saif . Optical Character Recognition based on Genetic Algorithms and Machine Learning. International Journal of Computer Applications. 172, 2 (Aug 2017), 33-36. DOI=10.5120/ijca2017915077
@article{ 10.5120/ijca2017915077,
author = { Arafat A. Muharram,Khaled M. G. Noaman,Ibrahim Abdulrab Ahmed,Jamil A. M. Saif },
title = { Optical Character Recognition based on Genetic Algorithms and Machine Learning },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 172 },
number = { 2 },
pages = { 33-36 },
doi = { 10.5120/ijca2017915077 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Arafat A. Muharram
%A Khaled M. G. Noaman
%A Ibrahim Abdulrab Ahmed
%A Jamil A. M. Saif
%T Optical Character Recognition based on Genetic Algorithms and Machine Learning%T
%J International Journal of Computer Applications
%V 172
%N 2
%P 33-36
%R 10.5120/ijca2017915077
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Pattern recognition is known to be one of the earliest applications of image processing. Genetic algorithm and Machine Learning have been used in this study to recognize English alphabets which are represented as matrix one and two dimensions. Genetic algorithm and machine learning were used in this paper to compare their efficiency and accuracy regarding concrete conditions, testing and evaluation results, it has ben got 95% for Genetic Algorithms and 94% for Machine Learning.
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