International Journal of Computational Intelligence Systems

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Volume 14, Issue 1, 2021, Pages 187 - 198

Online Handwritten Arabic Scripts Recognition Using Stroke-Based Class Labeling Scheme

Authors
Rabiaa Zitouni1, *, Hala Bezine2, Najet Arous1
1Laboratory LR-SITI ENIT University Tunis El Manar, B.P.37, Tunis, 1002, Tunisia
2Laboratory REGIM ENIS University sfax, B.P.1173, Sfax, 3038, Tunisia
*Corresponding author. Email: zitounirabiaa@yahoo.fr
Corresponding Author
Rabiaa Zitouni
Received 15 July 2020, Accepted 15 October 2020, Available Online 30 October 2020.
DOI
10.2991/ijcis.d.201024.001How to use a DOI?
Keywords
Beta-elliptic model; Fuzzy perceptual codes; Strokes classification; Spatial relations; Online handwriting recognition; Two-stage SVMs
Abstract

With the increasing availability of pen-based user interfaces, we often come upon multiple data sets of online handwritten scripts such as letters, words, etc., that are collected based on a viable interface. In this paper, we set forward a new method for online handwritten Arabic scripts recognition. Departing from the assumption that handwritten scripts are encoded as a set of strokes, the proposed approach relies first upon classifying strokes contained on the script and then recognizes the whole script. For stroke classification, an support vector machine (SVM) is trained with stroke features vectors obtained from the Beta-elliptic model and fuzzy elementary perceptual codes to obtain class stroke probabilities. The output of this SVM is combined with spatial relation vectors feeding to a second SVM to provide scripts level recognition. The proposed model has been tested on MAYASTROUN dataset. In order to obtain additional insight into the efficiency of the proposed approach, we performed further experiments on ADAB data set. The experimental results highlight its relevance by comfortably outperforming state-of-art systems.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
14 - 1
Pages
187 - 198
Publication Date
2020/10/30
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.201024.001How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Rabiaa Zitouni
AU  - Hala Bezine
AU  - Najet Arous
PY  - 2020
DA  - 2020/10/30
TI  - Online Handwritten Arabic Scripts Recognition Using Stroke-Based Class Labeling Scheme
JO  - International Journal of Computational Intelligence Systems
SP  - 187
EP  - 198
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201024.001
DO  - 10.2991/ijcis.d.201024.001
ID  - Zitouni2020
ER  -