国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Sample annotation is the key step in the applications of deep learning. In order to solve labeling problems of typical ground objects in UAV remote sensing images caused by the complex motion of UAV platform, insufficient illumination and complexity of object contours. In this paper,an improved live-wire algorithm was proposed and applied into image annotation of typical objects in UAV remote sensing images. The traditional Pal-King fuzzy edge detection method was improved by proposing a fuzzy membership function to over-come defects in gray coverage of traditional PAL-King membership function and the double threshold method was used to extract edge points. Moreover, the proposed fuzzy edge detection method was used to replace the Laplace edge detection algorithm in traditional live-wire method. The cost function was further optimized by increasing change characteristics of gradient amplitude between nodes to improve perfor-mance and continuity of edge detection and contour tracking. A large number of experiments show that the proposed method can detect and track object contours of UAV images with higher robustness and efficien-cy than that of traditional methods.