Handwritten Bangla Numeral and Basic Character Recognition Using Deep Convolutional Neural Network

Abstract

In this paper, the problem of recognizing handwritten

Bangla characters is addressed. Handwritten character

recognition is one of the most practiced tasks in computer

vision. Over the past few years Convolutional Neural Network

has produced the best results in case of English handwritten

character recognition. Although Bangla the official language of

Bangladesh and several Indian states with over 200 million

native speakers Bangla handwritten character recognition is

quite far behind.We present a 9 layer sequential Convolutional

Neural Network model to recognize 60 (10 numerals+ 50 basic

characters) Bangla handwritten characters. BanglaLekha-

Isolated dataset is used as train-validation set. A new dataset

of 6000 images is created for cross validation. Our proposed

model trained to recognize 60 characters achieves state-of-the-art

99.44% accuracy on BanglaLekha-Isolated dataset and 95.16%

accuracy on prepared test set. Experiments on recognizing Bangla

numerals separately also show state-of-the-art performance