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SAR target recognition based on active contour without edges

机译:基于无边缘主动轮廓的SAR目标识别

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摘要

A new method for synthetic aperture radar (SAR) tar-get recognition is proposed. This method is accomplished via the combination of active contour without edges, Hu invariant moments and support vector machine (SVM) classifier. Image segmentation is performed by using active contour without edges. Then seven Hu moments are extracted and normalized as feature vectors. Fi-nally, the SVM classifier is employed for data training and testing by means of MSTAR SAR images. To verify the performance of the proposed method, the traditional active contour (snakes) is used for comparison. The simulation results confirm the feasibi-lity and accuracy of the proposed method in SAR target recogni-tion.
机译:提出了一种合成孔径雷达(SAR)目标识别的新方法。该方法是通过无轮廓有效轮廓,Hu不变矩和支持向量机(SVM)分类器的组合来完成的。通过使用无边缘的活动轮廓进行图像分割。然后提取7个Hu矩并将其归一化为特征向量。最后,通过MSTAR SAR图像将SVM分类器用于数据训练和测试。为了验证所提出方法的性能,将传统的主动轮廓(蛇形)用于比较。仿真结果证实了该方法在SAR目标识别中的可行性和准确性。

著录项

  • 来源
    《系统工程与电子技术(英文版)》 |2017年第2期|276-281|共6页
  • 作者

    Rui Zhang; Min Zhang;

  • 作者单位

    School of Physics and Optoelectionic Engineering, Xidian University, Xi'an 710071, China;

    School of Physics and Optoelectionic Engineering, Xidian University, Xi'an 710071, China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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