DocumentCode :
2482599
Title :
Enhanced Bangla Character Recognition Using ANN
Author :
Upadhyay, Piu ; Barman, Sumana ; Bhattacharyya, Debnath ; Dixit, Manish
Author_Institution :
Comput. Sci. & Eng. Dept., Heritage Inst. of Technol., Kolkata, India
fYear :
2011
fDate :
3-5 June 2011
Firstpage :
194
Lastpage :
197
Abstract :
This paper describes how the Bangla characters are processed, trained and then recognized with the use of a neural network. The size and the font used for the characters are similar in both training and classification of the network. The images are first converted into grayscale and then to binary images. These images are then scaled to fit a pre-defined area. By extracting the characteristics points we get the feature vectors, which is simply a series of 0s and 1s of fixed length. Finally, an Artificial Neural Network is chosen for the training and classification process. It has been noticed that recognition decreases due to presence of touching characters in the text. So recognition is done here with isolated printed characters.
Keywords :
learning (artificial intelligence); natural language processing; neural nets; text analysis; artificial neural network; enhanced Bangla character recognition; isolated printed characters; network classification; network. training; touching characters; Communication systems; Decision support systems; ANN; OCR; binarization; data; recognition; system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2011 International Conference on
Conference_Location :
Katra, Jammu
Print_ISBN :
978-1-4577-0543-4
Electronic_ISBN :
978-0-7695-4437-3
Type :
conf
DOI :
10.1109/CSNT.2011.48
Filename :
5966434
Link To Document :
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