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

机译:使用Hahn和Charlier More的3D本地特征提取快速算法

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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,通过使用HAHN和Charlier矩来提取来自物体的3D本地特征。这些时刻具有计算来自图像中感兴趣区域的本地描述符。这可以通过改变Hahn和Charlier多项式的参数来实现。一种基于矩阵乘法的算法用于加速3D时刻的计算时间。实验结果已经说明了Hahn和Charlier时刻提取来自3D对象的任何区域的特征的能力。但是,我们在重建准确性方面观察了哈恩州的优越性。另外,与直接方法相比,所提出的算法在计算时间中产生急剧减少。

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