Fuzzy logic based handwritten character recognition

Author

Hanmandlu, M. ; Chakraborty, Shiladri

Author_Institution

Dept. of Comput. Eng., Multimedia Univ., Selongor

Volume

3

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

42

Abstract

This paper presents an innovative approach called box method for feature extraction for the recognition of handwritten characters. In this approach, the character image is partitioned into a fixed number of sub images called boxes. The features consist of normalized vector distance (γ) and angle (α) from each box to a fixed point. The recognition schemes used are back propagation neural network (BPNN) and fuzzy logic. The recognition rate is found to be around 100% with the fuzzy based approach on the standard database

Keywords

backpropagation; feature extraction; fuzzy logic; handwritten character recognition; image segmentation; neural nets; backpropagation neural network; box method; feature extraction; fuzzy logic; handwritten character recognition; image partitioning; normalized vector angle; normalized vector distance; Character recognition; Computer science; Feature extraction; Fuzzy logic; Handwriting recognition; Image databases; Multi-layer neural network; Neural networks; Optical character recognition software; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2001. Proceedings. 2001 International Conference on

Conference_Location

Thessaloniki

Print_ISBN

0-7803-6725-1

Type

conf

DOI

10.1109/ICIP.2001.958046

Filename

958046