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Shape detection by mathematical morphology techniques for radar target classification

机译:通过数学形态学技术进行形状检测以进行雷达目标分类

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This paper presents a process of knowledge Discovery from Data (KDD) applied on 2D Inverse Synthetic Aperture Radar (ISAR) images. This process is based on four crucial steps which are data acquisition, data pre-processing, data representation and data classification to make the final decision. We propose a new method for data representation based on combining mathematical morphology top-Hat, Thresholding and Watershed transformation for target shape extraction from ISAR images. Then, the feature vector is achieved by Fourier descriptors of each extracted target shape. And finally the classification results are obtained using Support Vector Machine (SVM) classifier. In the last section, experimental results are provided and discussed.
机译:本文介绍了一种应用于二维逆合成孔径雷达(ISAR)图像的数据发现知识(KDD)过程。该过程基于四个关键步骤,即数据获取,数据预处理,数据表示和数据分类以做出最终决定。我们提出了一种新的数据表示方法,该方法基于结合数学形态学top-Hat,阈值和分水岭变换从ISAR图像中提取目标形状。然后,通过提取每个目标形状的傅立叶描述符获得特征向量。最后,使用支持向量机(SVM)分类器获得分类结果。在最后一部分中,提供并讨论了实验结果。

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