作者：张帆, 靳晓妍

作者单位：湖南大学电气与信息工程学院，湖南 长沙 410082

关键词：移动激光;视频;图像识别;水位检测;目标跟踪

摘要：

针对图像处理检测水位方法中由于环境光线、水渍、杂物等干扰因素造成的测不准问题，提出一种结合移动激光与视频图像处理技术的方法，该方法通过提取并跟踪移动激光的光斑，识别出激光在背板与水面之间的移动轨迹，从而判断出图像中水位位置，并根据几何关系计算实际水位高度。对水电站真实水位视频进行检测实验，并与基于模板匹配的图像处理检测水位法进行对比，结果表明该方法的检测误差小于2.00 cm，证明该方法对光线强度不敏感，能有效排除污染和水体波动等干扰因素，从而充分证实该方法的有效性。

Embedded water level monitoring method based on video image
ZHANG Fan, JIN Xiaoyan
College of Electrical and Information Engineering of Hunan University, Changsha 410082, China
Abstract: The method of water level measurement based on image processing technology usually encounter the problem of low accuracy caused by the light from the outside environmental and debris floating on the water. A method combining movable laser technology and video image processing technology is proposed to solve this problem. By recognizing and tracking the moving laser spot, this method can obtain the trajectory of the moving laser between the backplane and the water surface. In this way, the position of the water level in the image can be caught, and the actual height of the water level can be calculated according to the geometric relationship. This method has been used to measure the water level in hydropower station, and the results are compared with the water level measurement method based on template matching algorithm. The results of comparison show that the measurement error of water level in this method is less than 2.00 cm. It indicates that this method is not sensitive to light intensity and can effectively eliminate the interference factors such as floating debris and water fluctuation. Thus, the effectiveness of this method is fully verified.
Keywords: mobile laser;video;image recognition;water level detection;target tracking
2022, 48(12):140-145  收稿日期: 2021-09-24;收到修改稿日期: 2021-12-08
基金项目:
作者简介: 张帆(1963-),男,副教授,硕士生导师,研究方向为嵌入式应用、运动控制
参考文献
[1] SINGH Y, RAGHUWANSHI S K, KUMAR S. Review on liquid-level measurement and level transmitter using conventional and optical techniques[J]. IETE Technical Review, 2019, 36(4): 329-340
[2] 安全, 范瑞琪. 常用水位传感器的比较和选择[J]. 水利信息化, 2014(3): 52-54
[3] LAN C, ZHOU Z, HE J, et al. A highly reliable liquid pressure sensor based on dual FBGs[M]. SPIE, 2008.
[4] KUMAR B, RAJITA G, MANDAL N. A review on capacitive-type sensor for measurement of height of liquid level[J]. Measurement and Control, 2014, 47(7): 219-224
[5] REZA S A, RIZA N A. Agile lensing-based non-contact liquid level optical sensor for extreme environments[J]. Optics Communications, 2010, 283(18): 3391-3397
[6] REZA S A, RIZA N A. A liquid lens-based broadband variable fiber optical attenuator[J]. Optics Communications, 2009, 282(7): 1298-1303
[7] SAHOO A K, UDGATA S K. A novel ANN-based adaptive ultrasonic measurement system for accurate water level monitoring[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 69(6): 3359-3369
[8] 蓝标. 高精度气介式超声波水位计的设计[J]. 水利信息化, 2012(2): 53-56
[9] 许笠, 王延乐, 华小军. 雷达水位计在水情监测系统中的应用研究[J]. 人民长江, 2014, 45(2): 74-77
[10] 陈翠, 刘正伟, 陈晓生, 等. 基于图像处理的水位信息自动提取技术[J]. 水利信息化, 2016(1): 48-55
[11] 仲志远. 一种基于图像识别的水位测量算法[J]. 国外电子测量技术, 2017, 36(6): 96-99
[12] 陆振邦, 任传胜. 基于嵌入式图像处理的水位监测系统设计[J]. 自动化与仪表, 2018, 33(11): 56-60
[13] 张振, 周扬, 王慧斌, 等. 标准双色水尺的图像法水位测量[J]. 仪器仪表学报, 2018, 39(9): 236-245
[14] 钟卓. 数字图像识别处理技术在小型水库水位观测中的应用[J]. 水利规划与设计, 2020(11): 44-47
[15] 江海洋, 刘林海, 李红石. 水位图像识别的场景问题处理方法和技术[J]. 水利信息化, 2020(1): 39-43
[16] 刘衎, 王剑平. 图像法水位检测研究进展[J]. 电子测量技术, 2021, 44(13): 104-113
[17] 邹洪波. 基于图像识别技术的水位测量误差分析[J]. 广西水利水电, 2020(4): 36-39
[18] 付耀衡, 彭泳卿, 刘鹏. 基于图像处理的液位测量技术研究现状与发展趋势[J]. 遥测遥控, 2020, 41(4): 18-27
[19] 王康. 基于嵌入式平台的目标跟踪系统研究[D]. 南京: 南京邮电大学, 2019.
[20] LIKAS A, VLASSIS N J, VERBEEK J. The global k-means clustering algorithm[J]. Pattern Recognition, 2003, 36(2): 451-461