Research on digital image recognition system based on multiple invariant moments theory and BP neural network

Author

Jian-ning, Han ; Ming-quan, Wang

Author_Institution

Sch. of Inf. & Commun. Eng., North Univ. of China, Taiyuan, China

Volume

3

fYear

2010

fDate

6-7 March 2010

Firstpage

399

Lastpage

403

Abstract

Based on the pattern recognition theory, principle processes of a digital image are described. To achieve de-noising, sharpening, binary transformation, edge extraction and other image processing of digital image, the image recognition system was programmed in C language. The system calculates the seven invariant moments as all characters of an image, recognizes an image by BP neural network.

Keywords

backpropagation; image recognition; neural nets; BP neural network; C language; binary transformation; denoising; digital image recognition system; edge extraction; image processing; multiple invariant moments theory; pattern recognition theory; sharpening; Character recognition; Data mining; Digital images; Feature extraction; Image recognition; Neural networks; Pattern recognition; Personal communication networks; Robotics and automation; System testing; BP neural network; digital image recognition system; multiple invariant moments theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on

Conference_Location

Wuhan

ISSN

1948-3414

Print_ISBN

978-1-4244-5192-0

Electronic_ISBN

1948-3414

Type

conf

DOI

10.1109/CAR.2010.5456719

Filename

5456719