Digital image-based water level recognizing system and method
Xu Xing1,2,3, Hong Tiansheng1,2,3, Yue Xuejun1,2,3,4, Cai Kun1,2,3, Huang Shuangping1,2,3, Liu Yongxin1,2,3
1.Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou, Guangdong 510642, China; 2.Division of Citrus Machinery, China Agriculture Research System, Guangzhou, Guangdong 510642, China; 3.College of Engineering, South China Agricultural University, Guangzhou, Guangdong 510642, China; 4.Faculty of Engineering and Surveying, University of Southern Queensland, Toowoomba QLD4350, Australia
Abstract：In order to monitor water level efficiently and provide instantaneous and effective information for guiding water conservancy and agriculture irrigation, a digital image-based water level recognizing system was designed. In the system, a red spherical buoy was installed on a rod which was fixed vertically in water. Since the water level was derived by change in the relative position of buoy, the water level information could be specified by processing the buoy images snatched by a digital camera. For an instantaneous water level could be obtained through a conversion formula between the spherical centre coordinates and the height of water level, an adaptive spherical buoy capturing algorithm for identifying the red region and extracting the characteristics of red sphere and a calculation and correction algorithm for the sphere centre coordinates were proposed. It was shown experimentally that the maximum error in measurement was 0.216 91 cm, which is far below 1cm error specified in the new edition of China National Standard(GB/T 50138—2010)under 6 megapixel camera, 71 cm shoot height, and 282 cm distance between the camera and the fixed rod. Importantly, the system needs no expansive water level gauge or complex sensors and is subject to a relatively low cost. Additionally, the system relies on non-contact measurement only, and unnecessarily affected by interference factors, such as water temperature, quality, sediment etc. This innovative system has a simple structure, can be installed conveniently and used easily, and it has an even better feasibility in water level monitoring sector.
徐兴,,, 洪添胜,,, 岳学军,,,, 蔡坤,,, 黄双萍,,, 刘永鑫,,. 基于数字图像的水位识别系统及其方法[J]. 排灌机械工程学报, 2014, 32(1): 33-39.
Xu Xing,,, Hong Tiansheng,,, Yue Xuejun,,,, Cai Kun,,, Huang Shuangping,,, Liu Yongxin,,. Digital image-based water level recognizing system and method. Journal of Drainage and Irrigation Machinery Engin, 2014, 32(1): 33-39.
陈立辉, 许伟强, 何青. 混合式水位测量方法的探究[J].水利信息化, 2012(1):55-59,72. Chen Lihui, Xu Weiqiang, He Qing. Research on an integrated measurement for water level[J]. Water Resources Informatization, 2012(1):55-59,72.(in Chinese)郑国伟,齐虹,林瑞全. 基于AT89S52单片机的双水箱水位控制系统设计[J]. 闽江学院学报, 2012, 33(2):77-81. Zheng Guowei,Qi Hong,Lin Ruiquan. The design of double water tank level control system on AT89S52 single-chip[J]. Journal of Minjiang University, 2012, 33(2):77-81.(in Chinese)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 Technologies, 2013, 32(8):53-55.(in Chinese)任明武,杨万扣,王欢, 等. 一种基于图像的水位自动测量新方法[J]. 计算机工程与应用, 2007,43(22):204-206. Ren Mingwu, Yang Wankou, Wang Huan, et al. New algorithm of automatic water level measurement based on image processing[J]. Computer Engineering and Applications, 2007,43(22):204-206.(in Chinese)姜晓玉, 花再军. 基于图像处理的水位自动读取[J]. 电子设计工程, 2011,19(23):23-25. Jiang Xiaoyu, Hua Zaijun. Water-level auto reading based on image processing[J]. Electronic Design Engineering, 2011,19(23):23-25.(in Chinese)Li Huiping, Wang Wei, Ma Fuchang, et al. The water level automatic measurement technology based on image processing[J]. Applied Mechanics and Materials, 2013,303/304/305/306:621-626.Poncos V, Teleaga D, Bondar C, et al. A new insight on the water level dynamics of the Danube Delta using a high spatial density of SAR measurements[J]. Journal of Hydrology, 2013,482:79-91.Wdowinski S, Kim Sang-Wan, Amelung F, et al. Space-based detection of wetlands′ surface water level changes from L-band SAR interferometry[J]. Remote Sensing of Environment, 2008,112(3):681-696.Li Xiuhong, Cheng Xiao, Gong Peng, et al. Design and implementation of a wireless sensor network-based remote water-level monitoring system[J]. Sensors, 2011,11(2):1706-1720.Singh I, Bansal M. Monitoring water level in agriculture using sensor networks[J]. International Journal of Soft Computing and Engineering, 2011,1(5):202-204.程琴,任海东.基于ZigBee的水库水位监测及远程控制系统[J].现代电子技术, 2013,36(13):68-70. Cheng Qin, Ren Haidong. System of reservoir level monitoring and remote control based on ZigBee[J]. Mo-dern Electronics Technique, 2013,36(13):68-70.(in Chinese)高晓亮, 王志良, 王馨, 等. 基于HSV空间的视频实时水位检测算法[J]. 郑州大学学报:理学版, 2010,42(3):75-79. Gao Xiaoliang, Wang Zhiliang, Wang Xin, et al. An algorithm of real-time water level detection via video based on HSV space[J]. Journal of Zhengzhou University: Natural Science Edition, 2010,42(3):75-79.(in Chinese)王晓红, 孙平, 徐卓, 等. 基于模式识别技术的色貌模型评价研究[J]. 光学技术,2012,38(5):573-578. Wang Xiaohong, Sun Ping, Xu Zhuo, et al. The research of color appearance models evaluation based on pattern recognition technology[J]. Optical Technique, 2012,38(5):573-578.(in Chinese)马林兰. 视觉与色彩[J]. 长春大学学报, 2004,14(1):93-94. Ma Linlan. Sight and colour[J]. Journal of Changchun University, 2004,14(1):93-94.(in Chinese)刘奇琦, 龚晓峰. 一种二值图像连通区域标记的新方法[J]. 计算机工程与应用, 2012,48(11):178-180. Liu Qiqi, Gong Xiaofeng. New algorithm for binary connected component labeling[J]. Computer Engineering and Applications, 2012,48(11):178-180.(in Chinese)