Abstract

 
 

References (4)



 


 



Handwritten Character Recognition Using Fuzzy Membership Function


Sumit Saha


Assam University - Department of Mathematics

T. Som


affiliation not provided to SSRN

February 21, 2012

IJETSE International Journal of Emerging Technologies in Sciences and Engineering, Vol. 5, No. 2, Dec 2011

Abstract:     
In the present paper, we have given a method to recognize a handwritten character by using Fuzzy membership function. Ten sample images of each character in matrix form are fused together to make one standard matrix of the character. The unknown character to be tested for identification is also converted to an image matrix and compared with each standard matrix and thereby recognized by using the Fuzzy scores generated. Several binary images have been tested to demonstrate the effectiveness of the system. This method improves the character recognition method of Chakraborty and Sil (2005) in terms of accuracy.

Number of Pages in PDF File: 5

Keywords: Fusion, Pattern score, Fuzzy membership function

JEL Classification: C45, C60, C69

Accepted Paper Series


Download This Paper

Date posted: February 22, 2012 ; Last revised: February 23, 2012

Suggested Citation

Saha, Sumit and Som, T., Handwritten Character Recognition Using Fuzzy Membership Function (February 21, 2012). IJETSE International Journal of Emerging Technologies in Sciences and Engineering, Vol. 5, No. 2, Dec 2011. Available at SSRN: http://ssrn.com/abstract=2009131 or http://dx.doi.org/10.2139/ssrn.2009131

Contact Information

Sumit Saha (Contact Author)
Assam University - Department of Mathematics ( email )
Silchar, Assam 788 011
India
T. Som
affiliation not provided to SSRN
Feedback to SSRN (Beta)


Paper statistics
Abstract Views: 376
Downloads: 93
Download Rank: 141,835
References:  4
Paper comments
No comments have been made on this paper

© 2013 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright
This page was processed by apollo1 in 0.422 seconds