Rohini Meher1 , Bidyutprabha Bhoi1 , Purnendu Mishra2*, Pankaj Kumar2
Abstract:
Character recognition is performed off-line after the writing or printing has been completed, as opposed to on-line recognition where the computer recognizes the characters as they are drawn. Both hand printed and printed characters may be recognized, but the performance is directly dependent upon the quality of the input documents. Artificial Neural Networks (ANNs) serve for the emulation of human thinking in computation to a meager, yet appreciable extent. Of the several fields wherein they have been applied, humanoid computing in general and pattern recognition in particular of increasing activity. ANNs have enjoyed considerable success in this area due to their humanoid qualities such as adapting to changes and learning from prior experience. Another approach of character recognition by the process of convolution individual character is convolved with dataset and character in the dataset with which maximum matching comes is assign to that character. In this paper both the methods are discussed with the simulation result.
https://doi.org/10.62226/ijarst20160389
PAGES : 635-639 | 73 VIEWS | 32 DOWNLOADS
Rohini Meher1 , Bidyutprabha Bhoi1 , Purnendu Mishra2*, Pankaj Kumar2 | Effective Character Recognition using ANN & Convolution Techniques. | DOI : https://doi.org/10.62226/ijarst20160389
Journal Frequency: | ISSN 2320-1126, Monthly | |
Paper Submission: | Throughout the month | |
Acceptance Notification: | Within 6 days | |
Subject Areas: | Engineering, Science & Technology | |
Publishing Model: | Open Access | |
Publication Fee: | USD 60 USD 50 | |
Publication Impact Factor: | 6.76 | |
Certificate Delivery: | Digital |