DocumentCode
3079799
Title
A framework for recognizing the hand written digits with multi-zone approach
Author
Rajiv, K. ; Saritha, T. ; Srikanth, Punugoti ; Sukesh, M.
Author_Institution
Dept. of CSE, Nalla Narasimha Reddy Educ. Soc.´s Group of Instn., Hyderabad, India
fYear
2013
fDate
26-28 Dec. 2013
Firstpage
1
Lastpage
4
Abstract
In this paper, we proposed a handwritten digit recognition system which uses multiple feature extraction methods. Here we extract the size features, and we proposed multi-zoning method. It is shown that multi zoning method is sufficient to achieve high recognition rates. Several combination schemes were tested, showing good results. By using this multi-zoning method we achieved a recognition rate of 97%, the highest one on the MNIST database.
Keywords
feature extraction; handwritten character recognition; image classification; MNIST database; handwritten digit recognition system; multiple feature extraction methods; multizoning method; Character recognition; Databases; Feature extraction; Handwriting recognition; Neural networks; Training; Vectors; Digit recognition; Handwritten; MNIST; database; multi-zone;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on
Conference_Location
Enathi
Print_ISBN
978-1-4799-1594-1
Type
conf
DOI
10.1109/ICCIC.2013.6724268
Filename
6724268
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