By Topic

Recognition of bangla basic characters using multiple classifiers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Das, P. ; St. Thomas'' Coll. of Eng. & Tech, Kolkata, India ; Paul, S. ; Ghoshal, R.

Character recognition is an important area in image processing and pattern recognition fields. A novel scheme for recognition of offline basic characters of Bangla using multiple classifiers is described here. Compared to English characters, there are different complex shaped characters in Bangla alphabet. Dealing with such a large number of characters with a suitably designed feature set is a challenging problem. Moreover, such a large variety of complex shaped characters, some of which have close resemblance, make the problem more difficult. Considering the complexity of the problem, present approach makes an attempt to identify the basic characters. We have adopted this hybrid approach because it is nearly impossible to find a set of stroke features which are sufficient to classify the characters. A prototype of the system is tested with a data set containing 4423 characters of different font and size. On average, the recognition accuracies for Binary tree based classifier and Multilayer perceptron [with backpropagation for learning] (MLP) are 90% above approximately.

Published in:

Computer and Communication Technology (ICCCT), 2011 2nd International Conference on

Date of Conference:

15-17 Sept. 2011