...
首页> 外文期刊>The Photogrammetric Record >Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation
【24h】

Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation

机译:基于动态聚类和粒子群算法的高分辨率图像道路矢量化

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

This paper introduces an innovative automatic road-vectorisation algorithm based on dynamic pixel clustering using particle swarm optimisation. A new cost function is designed to optimise the number and position of road keypoints and is capable of deriving road centrelines without considering geometric, spectral or topological characteristics in the road model. The algorithm is applied to different high-resolution images (IKONOS, QuickBird and aerial photographs) and is evaluated with respect to RMSE, correctness and completeness. Moreover, a new quality parameter is defined to evaluate a kinking effect in roads. Extraction of different road shapes with an acceptable precision in both urban and rural environments proves the efficiency of the algorithm in yielding complete road networks.
机译:本文介绍了一种创新的基于粒子群优化的动态像素聚类自动道路矢量化算法。设计了一种新的成本函数来优化道路关键点的数量和位置,并且能够在不考虑道路模型中的几何,光谱或拓扑特征的情况下得出道路中心线。该算法适用于不同的高分辨率图像(IKONOS,QuickBird和航空照片),并针对RMSE,正确性和完整性进行了评估。此外,定义了新的质量参数以评估道路的扭结效果。在城市和乡村环境中以可接受的精度提取不同的道路形状证明了该算法在产生完整道路网络方面的效率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号