严武凌, 邱亚峰. 基于区域霍夫变换的机弹分离初始信息提取研究[J]. 应用光学, 2021, 42(1): 65-70. DOI: 10.5768/JAO202142.0102003
引用本文: 严武凌, 邱亚峰. 基于区域霍夫变换的机弹分离初始信息提取研究[J]. 应用光学, 2021, 42(1): 65-70. DOI: 10.5768/JAO202142.0102003
YAN Wuling, QIU Yafeng. Research on initial information extraction of aircraft and missile separation based on regional Hough transformation[J]. Journal of Applied Optics, 2021, 42(1): 65-70. DOI: 10.5768/JAO202142.0102003
Citation: YAN Wuling, QIU Yafeng. Research on initial information extraction of aircraft and missile separation based on regional Hough transformation[J]. Journal of Applied Optics, 2021, 42(1): 65-70. DOI: 10.5768/JAO202142.0102003

基于区域霍夫变换的机弹分离初始信息提取研究

Research on initial information extraction of aircraft and missile separation based on regional Hough transformation

  • 摘要: 为提供机弹分离数值仿真的精准初始物理信息,提出了基于区域霍夫变换的导弹物理信息提取方案,利用高速摄像机提取视频帧中导弹弹身与弹尾处的标识圆圆心位置,并通过坐标变换计算出导弹的物理信息。在帧处理上,利用帧前后时间间隔短、速度矢量变化可以忽略的特点,提出基于区域霍夫变换的圆搜索算法。该算法针对实际中运动矢量在搜索窗口具有偏置而非均匀分布的特性,对搜索框进行固定移位,预测区域与实际区域的中心误差不超过5%,且耗时较传统算法减少41.6%以上,计算结果与实际结果平均误差不超过2.39%,同时还具有复杂背景的适应能力,满足方案时效性与精度需求。

     

    Abstract: In order to provide the accurate initial physical information for numerical simulation of aircraft and missile separation, a missile physical information extraction scheme based on regional Hough transformation was proposed, which used high-speed cameras to extract the positions of marking circle centers on the missile body and tail in the video frame, and calculated the physical information of missile through the coordinate transformation. In frame processing, according to short time interval and negligible change of velocity vector in the frames, a circle search algorithm based on regional Hough transformation was proposed. In view of the fact that the real motion vector is biased rather than uniformly distributed in search window, the search box was fixed shifted. The centering error between predicted region and actual region is less than 5%, the consuming time is reduced by more than 41.6% compared with the traditional algorithm, and the average error between calculated results and actual results does not exceed 2.39%. Also, this algorithm can adapt to the complex backgrounds and meet the timeliness and accuracy requirements of the program.

     

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