Multi-stage Off-line Arabic Handwriting Recognition Approach using Advanced Cascading Technique

Taraggy Ghanim, Mahmoud Khalil, Hazem Abbas

Abstract

Automatic Recognition of Arabic Handwriting is a pervasive field that has many challenging complications to solve. Such complications include big databases and complex computing activities. The proposed approach is a multi-stage cascading recognition system bases on applying Random Forest classifier (RF) to construct a forest of decision trees. The constructed decision trees split big databases to multiple smaller data-mined sets based on the most discriminating computed geometric and regional features. Each data-mined set include similar database classes. RF match each test image with one of the data-mined sets. Afterwards, the matching classes are sorted relative to test image using Pyramid Histogram of Gradients and Kullback-Leibler based ranking algorithm. Finally, the classification process is applied on the highly ranked matching classes to assign a class membership to test image. Adjusting the classification process to only consider the highly ranked database classes reduced the computing classification and enhanced the overall performance. The proposed approach was tested on IFN-ENIT Arabic database and achieved satisfactory results and enhanced sensitivity of decision trees to reach 93.5% instead of 86.5% (Ghanim et al., 2018).

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Paper Citation


in Harvard Style

Ghanim T., Khalil M. and Abbas H. (2019). Multi-stage Off-line Arabic Handwriting Recognition Approach using Advanced Cascading Technique.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 532-539. DOI: 10.5220/0007374605320539


in Bibtex Style

@conference{icpram19,
author={Taraggy Ghanim and Mahmoud Khalil and Hazem Abbas},
title={Multi-stage Off-line Arabic Handwriting Recognition Approach using Advanced Cascading Technique},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={532-539},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007374605320539},
isbn={978-989-758-351-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Multi-stage Off-line Arabic Handwriting Recognition Approach using Advanced Cascading Technique
SN - 978-989-758-351-3
AU - Ghanim T.
AU - Khalil M.
AU - Abbas H.
PY - 2019
SP - 532
EP - 539
DO - 10.5220/0007374605320539