VISUAL SALIENT SIFT KEYPOINTS DESCRIPTORS FOR AUTOMATIC TARGET RECOGNITION

被引:0
|
作者
Karine, Ayoub [1 ,3 ]
Toumi, Abdelmalek [3 ]
Khenchaf, Ali [3 ]
El Hassouni, Mohammed [1 ,2 ]
机构
[1] Mohammed V Univ Rabat, LRIT, Associated Unit CNRST URAC 29, Fac Sci, BP 1014 RP, Rabat, Morocco
[2] Mohammed V Univ Rabat, DESTEC, FLSHR, Rabat, Morocco
[3] ENSTA Bretagne, Lab STICC UMR CNRS 6285, F-29806 Brest 9, France
来源
PROCEEDINGS OF THE 2016 6TH EUROPEAN WORKSHOP ON VISUAL INFORMATION PROCESSING (EUVIP) | 2016年
关键词
Automatic target recognition; inverse synthetic aperture radar; SIFT; visual attention model; classification;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform (SIFT) method is used to extract the keypoints and their descriptors. Then, a local salient feature is built by considering only the keypoints located in the salient region. For the classification step, the support vector machines (SVM) classifier is adopted. To validate the proposed approach, ISAR images database which was collected from anechoic chamber is used.
引用
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页数:5
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