The Estimating For The Cloud Motion Based On The Feature Points Matching

To monitor the cloud movement and predict the movement trend of cloud in real time is the key technology to ensure the safe operation of tower solar thermal power system. However,the existed techniques for monitoring the state of cloud motion are expensive and the function are singleness. So this article carried out research on cloud monitoring methods by the technology of image processing combining with the Kalman filtering. To effectively monitor the movement trend of clouds over the solar system, at the same time make the cost reduction.Based on image processing technology, this paper presents an analysis method for real-time monitoring of cloud motion in mirror field. Firstly, using the adaptive median filtering combining with the adaptive Wiener filtering to preprocess the sky image for achieving the removal of noise effective,it is good to retain the characteristics of the sky image . Then, using the threshold segmentation to find the sun in image, using texture image combined with Otsu method to segment the whole image.Then remove the sun area to get clouds areas. Lastly, using the method Surf based on the feature points matching combining with the kalman filter to obtaining the optimal estimation of cloud motion velocity under ideal sky conditions, monitoring the solar system field clouds effectively, computing the speed in real time and predicting the speed in next time exactly.Through experiments showing, the method we proposed in our paper is practical and effective for monitoring the cloud motion in the sky over for the tower type solar mirror field.Whatever the segmentation for the image or the calibration of the cloud or the prediction of the cloud movement can all achieving to the desired goal. The results are preferably in accurate and real-time. In our paper we using the method of image processing and kalman filter combination provides an effective way for the monitoring and warning for the mirror field under the sky. So it will provide a reliable guarantee for the feed forward to the tower solar thermal power generation.