Research Article
A Hybrid Approach towards Cost Effective Model for Handwritten Character Recognition
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 95 - Issue 14 |
| Published: June 2014 |
| Authors: Nupur Chauhan, Manish Sharma, Pooja Singh |
10.5120/16666-6657
|
Nupur Chauhan, Manish Sharma, Pooja Singh . A Hybrid Approach towards Cost Effective Model for Handwritten Character Recognition. International Journal of Computer Applications. 95, 14 (June 2014), 36-39. DOI=10.5120/16666-6657
@article{ 10.5120/16666-6657,
author = { Nupur Chauhan,Manish Sharma,Pooja Singh },
title = { A Hybrid Approach towards Cost Effective Model for Handwritten Character Recognition },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 95 },
number = { 14 },
pages = { 36-39 },
doi = { 10.5120/16666-6657 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Nupur Chauhan
%A Manish Sharma
%A Pooja Singh
%T A Hybrid Approach towards Cost Effective Model for Handwritten Character Recognition%T
%J International Journal of Computer Applications
%V 95
%N 14
%P 36-39
%R 10.5120/16666-6657
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Handwritten character is gaining a lot of attention in the area of pattern recognition as its applications in various fields are increasing day by day. HCR system is providing us with a key factor to a paperless environment. Feature Extraction is a key part for a cost effective model for handwritten character recognition. Effective features improve the recognition rate and misclassification. A hybrid model provides better performance in comparison of the individual. Convolution neural networks are viewed to be more efficient to optimize the recognition ability of HCR system.
References
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