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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 - Number 14 |
| Year of Publication: 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
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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