Research on water level measurement based on image recognition for industrial boiler

Author

Sun Bin ; Changsheng Zhang ; Lun Li ; Jianping Wang

Author_Institution

Fac. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China

fYear

2014

fDate

May 31 2014-June 2 2014

Firstpage

1344

Lastpage

1348

Abstract

Bicolor water level gauge is the important equipment for industrial boiler. Machine recognition of water level image makes the traditional video monitoring system more intelligent. In this paper, the recognition algorithms such as improved BP neural network and feature matching are studied and compared. Experiments show that the recognition rate of latter approach is up to 100% with high identifying speed. Furthermore, a digital video level measurement system is designed based on CCD and FPGA.

Keywords

boilers; feature extraction; field programmable gate arrays; image recognition; level measurement; monitoring; neural nets; video surveillance; water meters; BP neural network; CCD; FPGA; bicolor water level gauge; digital video level measurement system; feature matching; image recognition; industrial boiler; machine recognition; recognition algorithms; video monitoring system; water level image; water level measurement; Algorithm design and analysis; Boilers; Digital images; Feature extraction; Field programmable gate arrays; Image recognition; Neurons; Digital Recognition; Feature Matching; Neural Network; Video-Based Water Level Gauge;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (2014 CCDC), The 26th Chinese

Conference_Location

Changsha

Print_ISBN

978-1-4799-3707-3

Type

conf

DOI

10.1109/CCDC.2014.6852375

Filename

6852375