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...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2017
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| Subjects: | |
| Online Access: | 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 |
| _version_ | 1848785879837966336 |
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| 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. |
| building | IIUM Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T17:00:10Z |
| format | Proceeding Paper |
| id | iium-62647 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:00:10Z |
| publishDate | 2017 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 Proceeding Paper 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 |
| 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 |
| title | 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_short | Off line Arabic handwritten character using neural network |
| title_sort | off line arabic handwritten character using neural network |
| topic | PJ6001 Arabic T Technology (General) |
| 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 |