基于改进亚像素边缘检测的弹丸特征点判读
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1南京理工大学瞬态物理国家重点实验室 南京 210094 2内蒙古北方重工业集团有限公司 包头 014033

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TP2

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国防基础科研计划项目(JCKYS2020606005)资助


Projectile feature point interpretation based on improved subpixel edge detection
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1 National Key Laboratory of Transient Physics, Nanjing University of Science and Technology, China, Nanjing 210094 2 Inner Mongolia Northern Heavy Industry Group Company Limited, China, Baotou 014033

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    摘要:

    针对传统弹丸图像判读效率低的问题,提出了一种基于改进边缘检测的图像自动判读方法,获得弹丸特征点坐标。在亚像素级别上利用Roberts模板求取图像梯度,寻找邻域内梯度最值绘制锚点,通过智能路线寻迹获得弹丸单像素边缘,采用矩理论求弹丸质心坐标。利用分辨率板检验改进边缘检测方法,并求取阴影图像中弹丸质心。实验结果表明,与传统方法相比,改进算法在边缘的连续性、定位精度上有较好的效果,将弹丸质心坐标的误差由6.7%降低到2.8%。

    Abstract:

    Aiming at the low efficiency of traditional projectile image interpretation, an image automatic interpretation method based on improved edge detection has been proposed to obtain the coordinates of projectile feature points. Roberts template is used to calculate the image gradient at the sub-pixel level, and the maximum gradient in the neighborhood is found as the anchor point. The single pixel edge of the projectile is obtained by the Smart Routing method and the centroid coordinates of the projectile are obtained by moment theory. Using the resolution plate to test the improved edge detection method, and the projectile centroid in shadow image is obtained. Experimental results show that, compared with the traditional method, the improved algorithm has better effect on edge continuity and positioning accuracy, and the error of the projectile centroid’s abscissa is reduced from 6.7 % to 2.8%.

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李 璐,罗红娥,刘亚军,孔筱芳,顾金良,夏言.基于改进亚像素边缘检测的弹丸特征点判读[J].电子测量技术,2022,45(5):146-151

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  • 在线发布日期: 2024-05-30
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