DetSegNet:一种基于检测和分割的高精度水尺水位检测网络

为了克服传统水位测量方法中水位边缘粗糙和检测精度不足的问题,提出了一种高精度的水尺水位检测网络——DetSegNet。DetSegNet在网络结构、损失函数等方面对YOLOv4和DeepLabv3+算法进行了改进,并将水尺刻度识别、水体区域分割、水位线检测和水位值计算等模块进行有效结合,实现了对水尺与水体交界区域的高效定位和精确分割。实验结果表明,DetSegNet在水尺图像数据集上的检测精度和速度均优于传统的检测方法； 现场测试表明,DetSegNet的水位检测误差小于1.cm,满足水文监测的精度要求。

DetSegNet: a high-precision water gauge level detection network based on detection and segmentation

To solve the problems of rough water-level edge and insufficient detection accuracy in existing algorithms, this paper proposes a high-accuracy water gauge level detection network, called DetSegNet. Unlike traditional methods that use a single network for the water gauge recognition and the water segmentation, DetSegNet innovates in the network structure, loss function, etc., by improving the YOLOv4 and DeepLabv3+ algorithms. It effectively integrates modules for water gauge scale recognition, water area segmentation, waterline detection, and water level calculation, achieving efficient localization and precise segmentation of the interface area between the water gauge and the water body. Experimental results show that DetSegNet surpasses existing algorithms in terms of detection accuracy and speed on water gauge image datasets. Field tests demonstrate that water level detection accuracy of this method is less than 1 cm, meeting the accuracy requirements of hydrological monitoring.