摘要
以无人机对风机叶片的巡检拍摄为应用背景,开展了风机叶片图像的拼接方法研究,提出了一种先进行背景分割然后进行图像网格化拼接的处理方法。通过深度学习U-Net算法,进行图像中风机主体部分的提取,该处理能够有效处理多视角大视差、目标背景特征点分布不均导致的风机叶片拼接困难的问题;在图像网格优化的过程中,基于保护风叶全局线性度的策略设计能量函数,优化得到的网格顶点对风机边缘的直线特征进行了有效保护。实现了多幅风机叶片的自然拼接,拼接得到的图像视觉效果畸变小、连续真实。
Taking UAV's patrol shooting of fan blades as the application background,the image stitching method of fan blade images is studied,a method of background segmentation and image gridding stitching is proposed.Through in-depth learning of U-Net algorithm,the main part of the fan is extracted from the image,which can effectively deal with the difficult problem of fan blade splicing caused by large parallax and uneven distribution of target background feature points.In the process of image grid optimization,the energy function is designed based on the strategy of protecting the global linearity of the fan blade,and the grid vertex is optimized to the edge of the fan.Linear features are effectively protected.The natural stitching of several fan blades is realized.The stitching image has small distortion and continuous reality.
作者
许恒雷
陈帅旗
宋勋
朱洺洁
XU Henglei;CHEN Shuaiqi;SONG Xun;ZHU Mingjie(Luneng New Energy(Group)Co.,Ltd,Beijing 100020,China;Beijing Institute of Electrical Engineering,Beijing 100854,China)
出处
《现代防御技术》
北大核心
2024年第4期123-129,共7页
Modern Defence Technology
基金
新能源场站海量数据深入挖掘与精益化运营关键技术研究(528060170002)。
