NNORC-a neural network for the optical character recognition

Author

Buttarazzi, Berta

Author_Institution

Dipartimento di Ingegneria Elettronica, Rome Univ., Italy

Volume

6

fYear

1994

fDate

27 Jun- 2 Jul 1994

Firstpage

4061

Abstract

Neural networks (NN) provide a promising approach to solve problems which are very hard for classical artificial intelligence, in fact due to their generalization capability and noise insensitivity, they have been applied to pattern recognition with very encouraging results. In this paper a multilayer backpropagation neural network for optical character recognition (NNORC) is presented. NNORC acquires data from a scanner system, recognizes the typewritten characters, assigns them an ASCII code and stores the informations in a computer file, accessible from any available program for further processing such as editing databases and cross-checking comparisons. The implemented system NNORC runs on PC 486-33 MHZ and starting from documents of omnifonts type of the Latin alphabet recognises 20 characters per second

Keywords

backpropagation; multilayer perceptrons; neural net architecture; optical character recognition; Latin alphabet; NNORC; multilayer backpropagation neural network; optical character recognition; typewritten characters; Artificial intelligence; Artificial neural networks; Character recognition; Multi-layer neural network; Neural networks; Optical character recognition software; Optical computing; Optical fiber networks; Optical noise; Pattern recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374864

Filename

374864