An Ensemble Learning Approach using Decision Fusion for the Recognition of Arabic Handwritten Characters

Rihab Dhief, Rabaa Youssef, Rabaa Youssef, Amel Benazza

2022

Abstract

The Arabic handwritten character recognition is a research challenge due to the complexity and variability of forms and writing styles of the Arabic alphabet. The current work focuses not only on reducing the complexity of the feature extraction step but also on improving the Arabic characters’ classification rate. First, we lighten the preprocessing step by using a grayscale skeletonization technique easily adjustable to image noise and contrast. It is then used to extract structural features such as Freeman chain code and Heutte descriptors. Second, a new model using the fusion of results from machine learning algorithms is built and tested on two grayscale images’ datasets: IFHCDB and AIA9K. The proposed approach is compared to state-of-the-art methods based on deep learning architecture and highlights a promising performance by achieving an accuracy of 97.97% and 92.91% respectively on IFHCDB and AIA9K datasets, which outperforms the classic machine learning algorithms and the deep neural network chosen architectures.

Paper Citation

in Harvard Style

Dhief R., Youssef R. and Benazza A. (2022). An Ensemble Learning Approach using Decision Fusion for the Recognition of Arabic Handwritten Characters. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-549-4, pages 51-59. DOI: 10.5220/0010839500003122

in Bibtex Style

@conference{icpram22,
author={Rihab Dhief and Rabaa Youssef and Amel Benazza},
title={An Ensemble Learning Approach using Decision Fusion for the Recognition of Arabic Handwritten Characters},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2022},
pages={51-59},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010839500003122},
isbn={978-989-758-549-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - An Ensemble Learning Approach using Decision Fusion for the Recognition of Arabic Handwritten Characters
SN - 978-989-758-549-4
AU - Dhief R.
AU - Youssef R.
AU - Benazza A.
PY - 2022
SP - 51
EP - 59
DO - 10.5220/0010839500003122