Offline handwritten digit recognition using triangle geometry properties

Draman @ Muda, Azah Kamilah and Azmi, Mohd Sanusi and Draman @ Muda, Noor Azilah and Arbain, Nur Atikah and Radzid, Amirul Ramzani (2018) Offline handwritten digit recognition using triangle geometry properties. International Journal of Computer Information Systems and Industrial Management Applications, 10. 087 - 097. ISSN 2150-7988

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Abstract

Offline digit handwritten recognition is one of the frequent studies that is being explored nowadays. Most of the digit characters have their own handwriting nature. Recognizing their patterns and types is a challenging task to do.Lately, triangle geometry nature has been adapted to identify the pattern and type of digit handwriting. However, a huge size of generated triangle features and data has caused slow performances and longer processing time. Therefore, in this paper, we proposed an improvement on triangle features by combining the ratio and gradient features respectively in order to overcome the problem. There are four types of datasets used in the experiment which are IFCHDB, HODA, MNIST and BANGLA. In this experiment, the comparison was made based on the training time for each dataset Besides, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) techniques are used to measure the accuracies for each of datasets in this study.

Item Type:	Article
Uncontrolled Keywords:	Digit recognition, Handwriting, Triangle feature, Triangle geometry
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Information and Communication Technology > Department of Software Engineeering
Depositing User:	Mohd. Nazir Taib
Date Deposited:	11 Feb 2019 07:42
Last Modified:	16 Aug 2023 14:27
URI:	http://eprints.utem.edu.my/id/eprint/21610
Statistic Details:	View Download Statistic

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