Complementary approaches built as web service for arabic handwriting OCR systems via amazon Elatic Map Reduce (EMR) Model
Joint Authors
Zaydan, Ayshah
Khemakhem, Mahir
Hamdi, Hasan
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 3 (31 May. 2018)10 p.
Publisher
Publication Date
2018-05-31
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Arabic Optical Character Recognition (OCR) as Web Services represents a major challenge for handwritten document recognition.
A variety of approaches, methods, algorithms and techniques have been proposed in order to build powerful Arabic OCR web services.
Unfortunately, these methods could not succeed in achieving this mission in case of large large quantity Arabic handwritten documents.
Intensive experiments and observations revealed that some of the existing approaches and techniques are complementary and can be combined to improve the recognition rate.
Designing and implementing these recent sophisticated complementary approaches and techniques as web services are commonly complex; they require strong computing power to reach an acceptable recognition speed especially in case of large quantity documents.
One of the possible solutions to overcome this problem is to benefit from distributed computing architectures such as cloud computing.
This paper describes the design and implementation of Arabic Handwriting Recognition as a web service (AHRweb service) based on the complementary approach K-Nearest Neighbor (KNN) /Support Vector Machine (SVM) (K-NN/SVM) via Amazon Elastic MapReduce (EMR) model.
The experiments were conducted on a cloud computing environment with a real large scale handwriting dataset from the Institute for Communications Technology (IFN)/ Ecole Nationale d’Ingénieur de Tunis (ENIT) IFN/ENIT database.
The J-Sim (Java Simulator) was used as a tool to generate and analyze statistical results.
Experimental results show that Amazon Elastic MapReduce (EMR) model constitutes a very promising framework for enhancing large AHRweb service performances.
American Psychological Association (APA)
Hamdi, Hasan& Khemakhem, Mahir& Zaydan, Ayshah. 2018. Complementary approaches built as web service for arabic handwriting OCR systems via amazon Elatic Map Reduce (EMR) Model. The International Arab Journal of Information Technology،Vol. 15, no. 3.
https://search.emarefa.net/detail/BIM-839243
Modern Language Association (MLA)
Hamdi, Hasan…[et al.]. Complementary approaches built as web service for arabic handwriting OCR systems via amazon Elatic Map Reduce (EMR) Model. The International Arab Journal of Information Technology Vol. 15, no. 3 (May. 2018).
https://search.emarefa.net/detail/BIM-839243
American Medical Association (AMA)
Hamdi, Hasan& Khemakhem, Mahir& Zaydan, Ayshah. Complementary approaches built as web service for arabic handwriting OCR systems via amazon Elatic Map Reduce (EMR) Model. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 3.
https://search.emarefa.net/detail/BIM-839243
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-839243