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Off line Arabic handwritten character using neural network

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.

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— 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.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 4119/62647
Uncontrolled Keywords: off-line handwriting, Arabic recognition, OCR, neural network, pattern recognition.
Subjects: P Language and Literature > PJ Semitic > PJ6001 Arabic
T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Prof. Dr Othman O. Khalifa
Date Deposited: 03 Apr 2018 15:10
Last Modified: 02 Oct 2018 17:20
URI: http://irep.iium.edu.my/id/eprint/62647

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