机车全动态包络线测量中的目标点自动识别算法研究
Research on automatic recognition algorithm of target points in locomotive dynamic envelope measurement
  
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中文摘要:
      针对机车动态限界图像中目标点自动识别的问题,提出一种基于双分辨力分析的目标点识别算法,解决了高分辨力图像对于多目标的搜索效率问题,并提出了一种自描述向量用于改进传统的RANSAC算法,以减少背景噪声的干扰,完成了不同限界图像目标点的单应矩阵的求解问题。最终实现高效且准确的目标点自动识别与匹配。
英文摘要:
Aiming at the problem of automatic recognition of target points in locomotive dynamic bounding images, a target point recognition algorithm based on dual-resolution analysis is proposed to solve the problem of searching efficiency for multi-target in high-resolution images. A self-describing vector is proposed to improve the traditional RANSAC algorithm to reduce the interference of background noise. The homography matrix of different target image points is solved. Finally, efficient and accurate automatic recognition and matching of target points can be achieved.
作者单位
邹志, 马骊群,甘晓川,樊晶晶 北京长城计量测试技术研究所北京 100095 
中文关键词:  动态限界  自动识别  双分辨率分析  自描述向量  RANSAC
英文关键词:dynamic gauge  auto recognition  dual resolution analysis  self-described vector  RANSAC
基金项目:
DOI:10.11823/j.issn.1674-5795.2018.04.09
引用本文:邹志, 马骊群,甘晓川,樊晶晶.机车全动态包络线测量中的目标点自动识别算法研究[J].计测技术,2018,38(5):.
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