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Frequency domain point cloud registration based on the Fourier transform

机译:基于傅立叶变换的频域点云注册

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摘要

Due to the limited measurement range and occlusion of single-line structured light, it is impossible to detect the side data of the whole part. It is proposed that point cloud registration method obtained from multiple rotations of parts in frequency domain by Fourier transform. In the process of point cloud registration, cross-section point cloud data are restored to the corresponding size matrix firstly. Secondly, Fourier transform is carried out to calculate the point cloud data. When calculating the rotation angle, the polar coordinate transformation is carried out at first, and then the cross power spectrum of the two matrices is obtained, so that the rotation and translation matrix of the point cloud can also be obtained. In this process, considering point cloud noise existence, the Sinc function is approximately replaced by the non-noise inverse Fourier transform of cross power spectrum, so that the noise has no influence on the determination of registration parameters in frequency domain registration. The registration accuracy of point cloud is checked by high precision rotation and multiple measurements of mobile platform. Finally, the rotation matrix and translation values are obtained. (C) 2019 Published by Elsevier Inc.
机译:由于测量范围和单线结构光的遮挡有限,因此无法检测整个部分的侧面数据。建议通过傅里叶变换从频域中零件的多重旋转获得的点云登记方法。在点云注册的过程中,首先将横截面点云数据恢复到相应的大小矩阵。其次,执行傅里叶变换以计算点云数据。在计算旋转角度时,首先执行极性坐标变换,然后获得两个矩阵的横频谱,从而也可以获得点云的旋转和转换矩阵。在该过程中,考虑到点云噪声存在,所以QUAR函数大致被跨功率谱的非噪声逆傅里叶变换替换,使得噪声对频域注册中的登记参数的确定没有影响。通过高精度旋转和移动平台进行多次测量来检查点云的注册精度。最后,获得旋转矩阵和转换值。 (c)2019年由elsevier公司发布

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