Handwritten character recognition by Fourier descriptors and neural network

Author

Chung, Yuk Ying ; To Wong, Man

Author_Institution

Space Centre for Satellite Navigation, Queensland Univ. of Technol., Brisbane, Qld., Australia

Volume

1

fYear

1997

fDate

4-4 Dec. 1997

Firstpage

391

Abstract

This paper describes a handwritten character recognition system by using a multi-layer perceptron with one hidden layer. Features extracted from the handwritten characters are Fourier descriptor (FD) and border transition technique (BTT). The FDs and border transition values are input to the neural network which is then trained by backpropagation. Test results indicate that FD combined with BTT can provide good recognition accuracy (96%) for handwritten numerals 0 to 9.

Keywords

Fourier transforms; backpropagation; character recognition; edge detection; feature extraction; handwriting recognition; image classification; multilayer perceptrons; Fourier descriptors; backpropagation; character classification; feature extraction; handwritten character recognition system; handwritten numerals; multilayer perceptron; neural network; recognition accuracy; test results; Australia; Character recognition; Computer networks; Feature extraction; Handwriting recognition; Multi-layer neural network; Multilayer perceptrons; Neural networks; Satellite navigation systems; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE

Conference_Location

Brisbane, Qld., Australia

Print_ISBN

0-7803-4365-4

Type

conf

DOI

10.1109/TENCON.1997.647338

Filename

647338