基于图像分割的云层测速方法

为了解决塔式太阳能电站镜场上空的云层遮挡问题,提出一种对镜场上空移动云层进行预测的测速方法。首先利用固定摄像机对云层图像进行采集,然后提取不同帧数的图像,并进行伽马变换、遗传算法图像分割、云层目标检测、运动云层匹配等处理,最后根据匹配得到的像素坐标计算云层的移动速度和方向。实验测试结果表明:与光流法的数据进行比较,显示图像分割方法计算量少,位置预测误差小。可见运用图像分割方法进行云测速是可行的,为塔式太阳能电站的云监测中云遮挡预判提供理论依据。

A Method to Measure Moving Velocity of Clouds Based on Image Segmentation

In order to solve the problem of cloud cover over the heliostat field of tower solar power station, a velocity measurement method was proposed which was used to forecast the moving cloud over the heliostat field. Firstly, the cloud image was captured by a fixed camera, then the images with different frames were extracted by software, and those operations were performed, such as gamma transformation, image segmentation based on genetic algorithm, cloud target detection, and motion cloud layer matching. Finally, the movement speed and direction of cloud layer was calculated according to the pixel coordinates obtained by the matching. The experimental results show that compared with the data of optical flow method, the image segmentation method requires less computation and the location prediction error is small. It is concluded that the image segmentation method for cloud velocity measurement is feasible, which can provide theoretical basis for cloud cover prediction in the cloud monitoring of tower solar power plant.