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Fast Algorithm for 3D Local Feature Extraction Using Hahn and Charlier Moments

机译:使用Hahn和Charlier矩的3D局部特征快速提取算法

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In this paper, we propose a fast algorithm to extract 3D local features from an object by using Hahn and Charlier moments. These moments have the property to compute local descriptors from a region of interest in an image. This can be realized by varying parameters of Hahn and Charlier polynomials. An algorithm based on matrix multiplication is used to speed up the computational time of 3D moments. The experiment results have illustrated the ability of Hahn and Charlier moments to extract the features from any region of 3D object. However, we have observed the superiority of Hahn moments in terms of reconstruction accuracy. In addition, the proposed algorithm produces a drastic reduction in the computational time as compared with straightforward method.
机译:在本文中,我们提出了一种快速算法,该算法通过使用Hahn和Charlier矩从对象中提取3D局部特征。这些时刻具有从图像中的感兴趣区域计算局部描述符的属性。这可以通过改变Hahn和Charlier多项式的参数来实现。使用基于矩阵乘法的算法来加快3D矩的计算时间。实验结果说明了Hahn和Charlier矩能够从3D对象的任何区域提取特征的能力。但是,我们已经观察到了哈恩矩在重构精度方面的优越性。此外,与简单方法相比,该算法大大减少了计算时间。

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