基于视频图像的水位监测方法研究
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摘要
为实现水位的实时精确监测,提出了一种基于视频图像的水位监测方法,该方法不识别水尺刻度与数字,而是利用水尺刻度对相机进行标定,用图像差分法提取水位变化区域,计算图像水位线坐标,根据相机标定结果算得实际水位高度。该方法算法简便、处理速度快、满足实时监测要求、受水尺刻度限制及污渍等外界环境的影响较小,可以较精确测得水位高度。研究选用两幅分辨率为640×480的图像进行模拟实验,在图像未满足要求的情况下测得水位平均误差小于0.5cm,当系统满足设计要求时测量精度会进一步提高,该方法可以较好地实现水位的实时精确监测。
In order to achieve real-time and accurate monitoring of the water level,a water level monitoring method based on image processing is proposed.Instead of recognizing the water gauge scale and numbers,the method uses the water gauge scale to calibrate the camera.It extracts the water level change area with the image difference method,calculates the image water level line coordinates,and obtains the actual water level height according to the camera calibration result.The method is simple in algorithm and fast in processing speed,thus it meets the requirements of real-time monitoring,and is less affected by the external environment such as water ruler scale limitation and stain,and can accurately measure the water level height.Two 640×480 pictures were selected for simulation experiments.An average water level error of less than0.5 cm was obtained when the image does not meet the requirements,but if the system meets the design requirements,the measurement accuracy will be further improved.The method can better realize real-time accurate monitoring of the water level.
In order to achieve real-time and accurate monitoring of the water level,a water level monitoring method based on image processing is proposed.Instead of recognizing the water gauge scale and numbers,the method uses the water gauge scale to calibrate the camera.It extracts the water level change area with the image difference method,calculates the image water level line coordinates,and obtains the actual water level height according to the camera calibration result.The method is simple in algorithm and fast in processing speed,thus it meets the requirements of real-time monitoring,and is less affected by the external environment such as water ruler scale limitation and stain,and can accurately measure the water level height.Two 640×480 pictures were selected for simulation experiments.An average water level error of less than0.5 cm was obtained when the image does not meet the requirements,but if the system meets the design requirements,the measurement accuracy will be further improved.The method can better realize real-time accurate monitoring of the water level.
引文
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[3]林瑞凤,徐海.基于图像传感器的明渠水位自动测量方法[J].传感器与微系统,2013,32(8):53-55.Lin Ruifeng,Xu Hai.Automatic measurement method for canals water level based on imaging sensor[J].Transducer and Microsystem Technol.,2013,32(8):53-55.
[4] Li Huiping,Wang Wei,Ma Fuchang,et al.The water level automatic measurement technology based on image processing[J].Appl.Mechanics and Mater.,2013,303-306:621-626.
[5] Lin F,Chang W Y,Lee L C,et al.Applications of image recognition for real-time water level and surface velocity[C]//IEEE Inter.Symp.on Multimedia,2014:259-262.
[6]兰华勇,严华.基于图像识别技术的水尺刻度提取方法研究[J].人民黄河,2015,37(3):28-30.Lan Huayong,Yan Hua.Research on application of the scale extraction of water-level ruler based on image recognition technology[J].Yellow River,2015,37(3):28-30.
[7] Gilmore T E, Birgand F, Chapman K W.Source and magnitude of error in an inexpensive image-based water level measurement system[J].J.of Hydrology,2013,496(496):178-186.
[8]石玉立,夏振,王林.基于IDL的视频图像水位检测新算法[J].科学技术与工程,2014,14(29):114-116.Shi Yuli,Xia Zhen,Wang Lin.A new algorithm of water level detection based on video image[J].Science Technol.and Engin.,2014,14(29):114-116.
[9] Richardson R M,Dalgliesh R M,Brennan T,et al.A neutron reflection study of the effect of water on the surface of float glass[J].J.of Non-Crystalline Solids,2001,292(1/3):93-107.
[10] Zhang Z,Wang X,Fan T H,et al.River surface target enhancement and background suppression for unseeded LSPIV[J].Flow Measurement and Instrumentation,2013,30:99-111.
[11] Cheng G,Chen J.A local feature descriptor based on local binary patterns[C]//Inter.Congress on IEEE Image and Signal Proc.,Bio Medical Engin.and Informatics(CISPBMEI),2016:251-258.
[12]何文浩,原魁,邹伟,等.自适应阈值的边缘检测算法及其硬件实现[J].系统工程与电子技术,2009,31(1):233-237.He Wenhao,Yuan Kui,Zou Wei,et al.Self-adaptive threshold edge detection and its implementation in hardware[J].Systems Engin.and Electron.,2009,31(1):233-237.
[13]张振,吕莉,石爱业,等.基于物像尺度变换的河流水面流场定标方法[J].仪器仪表学报,2017,38(9):2273-2281.Zhang Zhen,Lv Li,Shi Aiye,et al.River surface flow field calibration method based on object-image scaling[J].Chinese J.of Scientific Instrument,2017,38(9):2273-2281.
[14]黄战华,熊浩伦,朱猛,等.嵌入式水尺图像检测系统与判读算法研究[J].光电工程,2013,40(4):1-7.Huang Zhanhua,Xiong Haolun,Zhu Meng,et al.Embedded measurement system and interpretation algorithm for water gauge image[J].Opto-Electronic Engin.,2013,40(4):1-7.
[15] Otsu N.An automatic threshold selection method based on discriminate and least squares criteria[J].Denshi Tsushin Gakkai Ronbunshi,1979,63:349-356.