High-speed character recognition using a dual cellular neural network architecture (CNND)

Author

Szirányi, Tamás ; Csicsvári, József

Author_Institution

Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary

Volume

40

Issue

3

fYear

1993

fDate

3/1/1993 12:00:00 AM

Firstpage

223

Lastpage

231

Abstract

An effective character recognition procedure implemented on a new type of hardware system and using a new architecture called CNND is proposed. This CNND contains one or more analog cellular neural networks (CNNs) and some digital logic, combining the advantages of the fast analog CNN signal processing and the fast and easy decision capability of digital logic. It is shown that the CNND system can be used for recognition of multifont printed or handwritten characters and could recognize 100,000 char/s with a recognition rate of more than 95%. The more advantage of the system over competing types is that there is not an extra feature extraction procedure implemented in slow hardware

Keywords

analogue processing circuits; character recognition equipment; neural nets; CNND; analog cellular neural networks; character recognition procedure; decision capability; digital logic; dual cellular neural network architecture; feature extraction procedure; handwritten characters; recognition rate; Cellular neural networks; Character recognition; Charge coupled devices; Detectors; Filling; Handwriting recognition; Hardware; Image edge detection; Logic; Neural networks;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.222823

Filename

222823