Recognition of isolated handwritten Arabic characters

Almansari, Osamah Abdulrahman and Nik Hashim, Nik Nur Wahidah (2019) Recognition of isolated handwritten Arabic characters. In: 7th International Conference on Mechatronics Engineering, ICOM 2019; Putrajaya; Malaysia, 30 - 31 Oct 2019, Putrajaya, Malaysia.

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Abstract

The challenges that face the handwritten Arabic recognition are overwhelming such as different varieties of handwriting and few public databases available. Also, teaching the non-Arabic speaker at the young age is very difficult due to the unfamiliarity of the words and meanings. So, this project is focused on building a model of a deep learning architecture with convolutional neural network (CNN) and multilayer perceptron (MLP) neural network by using python programming language. This project analyzes the performance of a public database which is Arabic Handwritten Characters Dataset (AHCD). However, training this database with CNN model has achieved a test accuracy of 95.27% while training it with MLP model achieved 72.08%. Therefore, the CNN model is suitable to be used in the application device.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	7157/79643
Uncontrolled Keywords:	Arabic database; Character recognition; CNN handwriting; Recognition MLP
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Nik Nur Wahidah Nik Hashim
Date Deposited:	10 Jun 2020 10:35
Last Modified:	09 Jul 2020 12:45
URI:	http://irep.iium.edu.my/id/eprint/79643

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