DocumentCode :
3574226
Title :
High accuracy optical character recognition algorithms using learning array of ANN
Author :
Vani, B. ; Beaulah, M. Shyni ; Deepalakshmi, R.
Author_Institution :
Velammal Coll. of Eng. & Technol., CSE, Madurai, India
fYear :
2014
Firstpage :
1474
Lastpage :
1479
Abstract :
Optical Character recognition refers to the process of translating the handwritten or printed text into a format that is understood by the machines for the purpose of editing, searching and indexing. The Performance of the current OCR illustrates and explains the actual errors and imaging defects in recognition with illustrated examples. This paper aims to create an application interface for OCR using artificial neural network as a back end to achieve high accurate rate in recognition. The proposed algorithm using neural network concept provides a high accuracy rate in recognition of characters. The proposed approach is implemented and tested on isolated character database consisting of English characters, digits and keyboard special characters.
Keywords :
handwritten character recognition; learning (artificial intelligence); neural nets; optical character recognition; ANN; English characters; OCR; artificial neural network; digits; handwritten text; high accuracy optical character recognition algorithms; imaging defects; isolated character database; keyboard special characters; learning array; neural network concept; printed text; Arrays; Artificial neural networks; Character recognition; Computers; Neurons; Optical character recognition software; Artificial Neural Networks; BPN; OCR; image digitization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on
Print_ISBN :
978-1-4799-2395-3
Type :
conf
DOI :
10.1109/ICCPCT.2014.7054772
Filename :
7054772
Link To Document :
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