Off line Arabic handwritten character using neural network

— Character Recognition (CR) considered as one of the most important in the field of pattern recognition. The ultimate objectives of the Optical Character Recognition (OCR) system is to simulate the capability of reading, hence the OCR considered as artificial intelligence. In this paper, a char...

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Main Authors:	Shamsan, Ehab A., Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Hamdan, H G Muhammad
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2017
Subjects:	PJ6001 Arabic T Technology (General)
Online Access:	http://irep.iium.edu.my/62647/ http://irep.iium.edu.my/62647/ http://irep.iium.edu.my/62647/ http://irep.iium.edu.my/62647/1/62647_Off%20line%20Arabic%20handwritten%20character.pdf http://irep.iium.edu.my/62647/7/62647_Off%20line%20Arabic%20handwritten%20character%20using%20neural%20network_scopus%20CONF.pdf

id	iium-62647
recordtype	eprints
spelling	iium-626472018-10-02T09:20:29Z http://irep.iium.edu.my/62647/ Off line Arabic handwritten character using neural network Shamsan, Ehab A. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Hamdan, H G Muhammad PJ6001 Arabic T Technology (General) — Character Recognition (CR) considered as one of the most important in the field of pattern recognition. The ultimate objectives of the Optical Character Recognition (OCR) system is to simulate the capability of reading, hence the OCR considered as artificial intelligence. In this paper, a character-handwritten recognition for the Arabic language is developed. The main aim of the system is to save time and effort Arabic OCR. In addition, to be the alternative of the typing manual due to provide it fast and reliable. The system has four main stages; preprocessing, segmentation, feature extraction, classification, and recognition. The system is off-line and depends on the image acquisition. So, after acquitted the image has to go through the main stages. The Neural Network used as a classifier. The proposed system is able to recognize as many characters as can with high accuracy rate. In addition, it is focusing on the character that has similarities and the system will also be considered about the number of dots and its position, and the connected components. IEEE 2017-11-28 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/62647/1/62647_Off%20line%20Arabic%20handwritten%20character.pdf application/pdf en http://irep.iium.edu.my/62647/7/62647_Off%20line%20Arabic%20handwritten%20character%20using%20neural%20network_scopus%20CONF.pdf Shamsan, Ehab A. and Khalifa, Othman Omran and Hassan Abdalla Hashim, Aisha and Hamdan, H G Muhammad (2017) Off line Arabic handwritten character using neural network. In: 4th IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) 2017, 28th-30th November 2017, Putrajaya, Malaysia. http://doi.org/10.1109/ICSIMA.2017.8312026 10.1109/ICSIMA.2017.8312026
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	PJ6001 Arabic T Technology (General)
spellingShingle	PJ6001 Arabic T Technology (General) Shamsan, Ehab A. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Hamdan, H G Muhammad Off line Arabic handwritten character using neural network
description	— Character Recognition (CR) considered as one of the most important in the field of pattern recognition. The ultimate objectives of the Optical Character Recognition (OCR) system is to simulate the capability of reading, hence the OCR considered as artificial intelligence. In this paper, a character-handwritten recognition for the Arabic language is developed. The main aim of the system is to save time and effort Arabic OCR. In addition, to be the alternative of the typing manual due to provide it fast and reliable. The system has four main stages; preprocessing, segmentation, feature extraction, classification, and recognition. The system is off-line and depends on the image acquisition. So, after acquitted the image has to go through the main stages. The Neural Network used as a classifier. The proposed system is able to recognize as many characters as can with high accuracy rate. In addition, it is focusing on the character that has similarities and the system will also be considered about the number of dots and its position, and the connected components.
format	Conference or Workshop Item
author	Shamsan, Ehab A. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Hamdan, H G Muhammad
author_facet	Shamsan, Ehab A. Khalifa, Othman Omran Hassan Abdalla Hashim, Aisha Hamdan, H G Muhammad
author_sort	Shamsan, Ehab A.
title	Off line Arabic handwritten character using neural network
title_short	Off line Arabic handwritten character using neural network
title_full	Off line Arabic handwritten character using neural network
title_fullStr	Off line Arabic handwritten character using neural network
title_full_unstemmed	Off line Arabic handwritten character using neural network
title_sort	off line arabic handwritten character using neural network
publisher	IEEE
publishDate	2017
url	http://irep.iium.edu.my/62647/ http://irep.iium.edu.my/62647/ http://irep.iium.edu.my/62647/ http://irep.iium.edu.my/62647/1/62647_Off%20line%20Arabic%20handwritten%20character.pdf http://irep.iium.edu.my/62647/7/62647_Off%20line%20Arabic%20handwritten%20character%20using%20neural%20network_scopus%20CONF.pdf
first_indexed	2023-09-18T21:28:46Z
last_indexed	2023-09-18T21:28:46Z
_version_	1777412369493786624

Off line Arabic handwritten character using neural network

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