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A Fourier Descriptor of 2D Shapes Based on Multiscale Centroid Contour Distances Used in Object Recognition in Remote Sensing Images

机译:基于多尺度质心轮廓距离的二维形状的傅立叶描述子在遥感图像目标识别中的应用

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摘要

A shape descriptor is an effective tool for describing the shape feature of an object in remote sensing images. Researchers have put forward a lot of excellent descriptors. The discriminability of some descriptors is very strong in the experiments, but usually their computational cost is large, which makes them unsuitable to be used in practical applications. This paper proposes a new descriptor-FMSCCD (Fourier descriptor based on multiscale centroid contour distance)—which is a frequency domain descriptor based on the CCD (centroid contour distance) method, multiscale description, and Fourier transform. The principle of FMSCCD is simple, and the computational cost is very low. What is commendable is that its discriminability is still strong, and its compatibility with other features is also great. Experiments on three databases demonstrate its strong discriminability and operational efficiency.
机译:形状描述符是用于描述遥感图像中对象形状特征的有效工具。研究人员提出了许多出色的描述符。在实验中,某些描述符的可分辨性非常强,但通常它们的计算量很大,这使其不适合在实际应用中使用。本文提出了一种新的描述符-FMSCCD(基于多尺度质心轮廓距离的傅里叶描述符),它是一种基于CCD(质心轮廓距离)方法,多尺度描述和傅里叶变换的频域描述符。 FMSCCD的原理很简单,计算成本很低。值得称赞的是,它的可分辨性仍然很强,并且与其他功能的兼容性也很好。在三个数据库上进行的实验证明了其强大的可识别性和运营效率。

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