Convolutional neural network based handwritten Bengali and Bengali-English mixed numeral recognition

Akhand, M. A. H and Ahmed, Mahtab and Rahman, M.M. Hafizur (2016) Convolutional neural network based handwritten Bengali and Bengali-English mixed numeral recognition. International Journal of Image, Graphics and Signal Processing (IJIGSP), 8 (9). pp. 40-50. ISSN 2074-9074 E-ISSN 2074-9082

PDF - Published Version Restricted to Repository staff only Download (1MB) | Request a copy

Abstract

Recognition of handwritten numerals has gained much interest in recent years due to its various potential applications. Bengali is the fifth ranked among the spoken languages of the world. However, due to inherent difficulties of Bengali numeral recognition, a very few study on handwritten Bengali numeral recognition is found with respect to other major languages. The existing Bengali numeral recognition methods used distinct feature extraction techniques and various classification tools. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this paper, we have investigated a CNN based Bengali handwritten numeral recognition scheme. Since English numerals are frequently used with Bengali numerals, handwritten Bengali-English mixed numerals are also investigated in this study. The proposed scheme uses moderate pre-processing technique to generate patterns from images of handwritten numerals and then employs CNN to classify individual numerals. It does not employ any feature extraction method like other related works. The proposed method showed satisfactory recognition accuracy on the benchmark data set and outperformed other prominent existing methods for both Bengali and Bengali-English mixed cases.

Item Type:	Article (Journal)
Additional Information:	6724/52028
Uncontrolled Keywords:	Image Pre-processing, Convolutional Neural Network, Bengali Numeral, Handwritten Numeral Recognition
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
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:	30 Sep 2016 09:52
Last Modified:	30 Sep 2016 09:52
URI:	http://irep.iium.edu.my/id/eprint/52028

Actions (login required)

View Item