Title :
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
fDate :
May 31 2014-June 2 2014
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;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852375
