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
