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首页> 外文期刊>Pattern Analysis and Applications >Statistical moments calculated via integral images in application to landmine detection from Ground Penetrating Radar 3D scans
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Statistical moments calculated via integral images in application to landmine detection from Ground Penetrating Radar 3D scans

机译:通过积分图像计算出的统计矩应用于从探地雷达3D扫描探测地雷中

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摘要

Under study is an application of Ground Penetrating Radar (GPR) to landmine detection problem. We focus on the detection of antitank mines carried out in the 3D GPR images, so-called C-scans, by means of a machine learning approach. In that approach, we particularly pursue a technique for fast extraction of image features based on an initial calculation of multiple integral images. This allows later to calculate each feature in constant time, regardless of the scanning window position and size. The features we study are statistical moments formulated in their 3D variant. We present a comparison of detection results for different sizes and parameterizations of feature sets. All results are obtained from a prototype GPR system of our original construction in terms of both hardware and software.
机译:正在研究的是探地雷达在探雷问题中的应用。我们专注于通过机器学习方法在3D GPR图像中进行的反坦克地雷的检测,即所谓的C扫描。在这种方法中,我们特别追求一种基于多个积分图像的初始计算来快速提取图像特征的技术。这样,以后无论扫描窗口的位置和大小如何,都可以在恒定时间内计算出每个特征。我们研究的功能是以其3D变体形式表示的统计矩。我们对特征集的不同大小和参数化的检测结果进行了比较。所有结果都是从我们原始结构的GPR原型系统获得的,包括硬件和软件。

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