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VISUAL SALIENT SIFT KEYPOINTS DESCRIPTORS FOR AUTOMATIC TARGETRECOGNITION

Authors
  • Karine, Ayoub
  • Toumi, Abdelmalek
  • Khenchaf, Ali
  • Hassouni, Mohammed El
Publication Date
Oct 25, 2016
Source
HAL-UPMC
Keywords
Language
English
License
Unknown
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Abstract

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 featureextraction to describe precisely an aircraft target from ISARimages. In our approach, a visual attention model is adoptedto separate the salient regions from the background. Afterthat, the scale invariant feature transform (SIFT) method isused to extract the keypoints and their descriptors. Then, alocal salient feature is built by considering only the keypointslocated in the salient region. For the classification step, thesupport vector machines (SVM) classifier is adopted. To validatethe proposed approach, ISAR images database whichwas collected from anechoic chamber is used.

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