Handwritten Bangla numeral recognition using deep long short term memory

Ahmed, Mahtab and Akhand, M. A. H and Rahman, M.M. Hafizur (2017) Handwritten Bangla numeral recognition using deep long short term memory. In: 2016 6th International Conference on Information and Communication Technology for The Muslim World, Nov. 22 ~ 24, 2016, Jakarta, Indonesia.

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Abstract

Recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. Bangla is a major language in Indian subcontinent and is the first language of Bangladesh; but unfortunately, study regarding handwritten Bangla numeral recognition (HBNR) is very few with respect to other major languages such as English, Roman etc. Some noteworthy research works have been conducted for recognition of Bangla handwritten numeral using artificial neural network (ANN) as ANN and its various updated models are found efficient for classification task. The aim of this study is to develop a better Bangla handwritten numeral recognition system and hence investigated deep architecture of Long Short Term Memory (LSTM) method. LSTM is a variant of recurrent neural networks (RNN) and is applied efficiently for image classification with its distinct features. The proposed HBNR-LSTM normalizes the written numeral images first and then employs two layers of LSTM to classify individual numerals. Unlike other methods, it does not employ any feature extraction technique. Benchmark dataset with 22000 hand written numerals with different shapes, sizes and variations are used in this study. The proposed method is shown satisfactory recognition accuracy and outperformed other prominent exiting methods.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	6724/54935
Uncontrolled Keywords:	Bangla handwritten numeral, recurrent neural network, long short term memory, deep neural networks.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr. M.M. Hafizur Rahman
Date Deposited:	10 Mar 2017 16:25
Last Modified:	05 Jun 2017 09:01
URI:	http://irep.iium.edu.my/id/eprint/54935

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