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Approach for Arabic Handwritten Image Processing: Case of Text Detection in Degraded Documents

by Youssef Boulid, Mohamed Youssfi Elkettani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 14
Year of Publication: 2014
Authors: Youssef Boulid, Mohamed Youssfi Elkettani
10.5120/17758-8891

Youssef Boulid, Mohamed Youssfi Elkettani . Approach for Arabic Handwritten Image Processing: Case of Text Detection in Degraded Documents. International Journal of Computer Applications. 101, 14 ( September 2014), 35-42. DOI=10.5120/17758-8891

@article{ 10.5120/17758-8891,
author = { Youssef Boulid, Mohamed Youssfi Elkettani },
title = { Approach for Arabic Handwritten Image Processing: Case of Text Detection in Degraded Documents },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 14 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 35-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number14/17758-8891/ },
doi = { 10.5120/17758-8891 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:31:41.184110+05:30
%A Youssef Boulid
%A Mohamed Youssfi Elkettani
%T Approach for Arabic Handwritten Image Processing: Case of Text Detection in Degraded Documents
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 14
%P 35-42
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This study presents a new approach for processing of Arabic handwritten documents based on the extraction of characteristics and mechanisms involved in the process of human visual perception. The architecture which has been developed is based on the concept of multi-agent systems, allowing the integration of different stages of character recognition process in a cooperative way. This is illustrated using as example the prepossessing of binary noisy document. Therefore, a method was proposed, in order to distinguish between text and non-text components, using a new geometric primitives extracted from the analysis of the characteristics of Arabic script. Results show pixel-level precision and recall respectively of 98% and 93% for noise removal. This proves the effectiveness of the proposed approach in processing degraded documents and, consequently, improving the recognition performance.

References
  1. Farahmand, A. , Sarrafzadeh, A. , & Shanbehzadeh, J. (2013). Document Image Noises and Removal Methods. In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 1)
  2. Haji, M. , Bui, T. D. , & Suen, C. Y. (2012). Removal of noise patterns in handwritten images using expectation maximization and fuzzy inference systems. Pattern Recognition, 45(12), 4237-4249
  3. Agrawal, M. , & Doermann, D. (2011, September). Stroke-like pattern noise removal in binary document images. In Document Analysis and Recognition (ICDAR), 2011 International Conference on (pp. 17-21). IEEE
  4. Agrawal, M. , & Doermann, D. (2013). Clutter noise removal in binary document images. International Journal on Document Analysis and Recognition (IJDAR),16(4), 351-369
  5. Shi, Z. , Setlur, S. , & Govindaraju, V. (2011, September). Image enhancement for degraded binary document images. In Document Analysis and Recognition (ICDAR), 2011 International Conference on (pp. 895-899). IEEE
  6. Bahaghighat, M. K. , & Mohammadi, J. (2012). Novel Approach for Baseline Detection and Text Line Segmentation. International Journal of Computer Applications, 51(2)
  7. MacQueen, J. (1967, June). Some methods for classification and analysis of multivariate observations. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, No. 14, pp. 281-297)
  8. G. Borgefors. Distance transformations in digital images. Comput. Vision Graph. Image Process. , 34(3):344–371,1986
  9. Vincent, L. (1993). Morphological grayscale reconstruction in image analysis: applications and efficient algorithms. Image Processing, IEEE Transactions on, 2(2), 176-201
  10. Dehaene, S. (2007). Neurones de la lecture (Les): La nouvelle science de la lecture et de son apprentissage. Odile Jacob
  11. Eglin, V. , Bres, S. , & Emptoz, H. (1999). Structuration de documents par repérage de zones d'intérêt. TS. Traitement du signal, 16(3), 217-239.
  12. Heutte, L. , Nosary, A. , & Paquet, T. (2004). A multiple agent architecture for handwritten text recognition. Pattern Recognition, 37(4), 665-674
Index Terms

Computer Science
Information Sciences

Keywords

Stroke width Intersections Multi-agent systems Distance transform

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