Recognition of Isolated Handwritten Arabic Characters

被引：4

作者：

Almansari, Osamah Abdulrahman ^{[1
]}

Hashim, Nik Nur Wahidah Nik ^{[1
]}

机构：

[1] Int Islamic Univ Malaysia, Dept Mechatron Engn, Kuala Lumpur, Malaysia

来源：

2019 7TH INTERNATIONAL CONFERENCE ON MECHATRONICS ENGINEERING (ICOM) | 2019年

关键词：

Handwriting Recognition; MLP; Arabic Database; CNN; character recognition;

D O I：

10.1109/icom47790.2019.8952035

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：107 / 111

页数：5