Rain gauge horizontal monitoring system based on image processing and detection method thereof

Abstract

The invention discloses a rain gauge horizontal monitoring system based on image processing and a detection method thereof. The system comprises a camera aligned with a detected gradienter. The outputend of the camera is electrically connected with a processor, and the processor is equipped with an image acquisition module, an image processing module and an angle judgment module. The image acquisition module is used for reading a gradienter image acquired by the camera into the image processing module through an image reading function in a computer vision image processing library OpenCV and modifying a pixel value of the acquired image and acquiring attribute information of the image. The image processing module is used for carrying out smooth filtering on the picture obtained by the image acquisition module, then carrying out Hough circle detection, and then drawing an N-S trend straight line passing through the circle center of the gradienter in a computer vision image processing library OpenCV. The angle judgment module is used for judging the deflection direction of the bubbles. The human eye observation level is converted into the analysis picture recognition level, and compared with manual observation, time and labor are saved, and the cost is saved.

Description

technical field [0001] The invention relates to an image processing-based rain gauge level monitoring system and a detection method thereof, belonging to the field of meteorological instrument working state monitoring. Background technique [0002] Reliable precipitation data is crucial to regional and global climate and hydrological research, and reliable precipitation data is critical to regional and global climate and hydrological research and is widely used. In order for the rain gauge to accurately measure the rainfall, the rain gauge needs to be kept level, and a level is required for monitoring. The level reads data manually, without a data interface connected to the computer, and cannot directly display the readings. The accuracy of manual readings is low. The error is large, and the reliability of level detection is poor. With the development of artificial intelligence, automatic instrument recognition using computer vision technology has become an important applic...

AI Technical Summary

Problems solved by technology

In order for the rain gauge to accurately measure the rainfall, the rain gauge needs to be kept level, and a level is required for monitoring. The level reads data manually, without a data interface connected to the computer, and cannot directly display the readings. The accuracy of manual readings is low. The error is large and the reliability of level detection is poor

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