基于OpenCV与图像处理的水位自动识别方法研究及应用

Research and Application of Automatic Water Level Recognition Method Based on OpenCV and Image Processing

摘要: 水位监测在水资源管理、防洪减灾、水环境评价等水利相关工作中具有重要的参考意义和应用价值。传统的人工观测和水位计监测方法耗时耗力，且存在人身安全风险，因此本文旨在通过图像处理法实现水位的自动识别，以提升监测效率和安全性。方法上，本文基于OpenCV库设计了一套水位识别系统，包括图像预处理、边缘检测、线条提取和数字识别等步骤。实验结果表明，该方法能够自动识别水尺图像中的水位高度，平均误差在可接受范围内，处理速度快，解放了大量人工资源。结论显示，该方法为智能化水位监测提供了可行方案，但受图像质量和拍摄角度影响，后续仍有改进空间。

Abstract: Water level monitoring holds significant reference value and application importance in water-related tasks such as water resources management, flood control and disaster reduction, and water environment assessment. Traditional manual observation and water gauge monitoring methods are time-consuming, labor-intensive, and pose personal safety risks. Therefore, this study aims to achieve automatic water level recognition through image processing methods to enhance monitoring efficiency and safety. Methodologically, this paper designs a water level recognition system based on the OpenCV library, which includes steps such as image preprocessing, edge detection, line extraction, and digit recognition. Experimental results indicate that this method can automatically identify the water level height from staff gauge images, with an average error within an acceptable range. The processing speed is fast, freeing up substantial human resources. In conclusion, the method provides a feasible solution for intelligent water level monitoring. However, its performance is influenced by image quality and shooting angle, indicating areas for future improvement.