Landmine Detection in 3D Images from Ground Penetrating Radar Using Haar-Like Features

被引：0
|
作者：
Klesk, Przemyslaw [1 ]
Godziuk, Andrzej [2 ]
Kapruziak, Mariusz [1 ,2 ]
Olech, Bogdan [1 ,2 ]
机构：
[1] West Pomeranian Univ Technol, Fac Comp Sci, Ul Zolnierska 49, PL-71210 Szczecin, Poland
[2] Autocomp Management, PL-70651 Szczecin, Poland
来源：
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I | 2013年 / 7894卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A prototype landmine detecting vehicle is presented. The vehicle is equipped with a Ground Penetrating Radar working in the frequency domain. The device collects 3D images defined over coordinates system: along track x across track x time, where the time (which can be associated with the depth) is obtained from frequency measurements via FFT. Learning of the detector is carried out by a boosting algorithm and is based on our proposition of 3D Haar-like features. Algorithmic details and experimental results are described, in particular: obtained accuracy, sensitivity, false-alarms rate and ROC curve.
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页码：559 / +
页数：3
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