基于伪特征四边形的三维点云配准算法
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河北省高等学校科学技术研究项目(No.ZD2022114);唐山市应用基础研究项目(No.21130212C);教育部产学合作协同育人项目(No.220804992272302)资助。


3D point cloud registration algorithm based on pseudo feature quadrilateral
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    摘要:

    :为解决传统描述符算法在进行圆孔局部配准时存在精度低、耗时长的问题,提出了一种通过借助构建伪特征四边形实现圆孔三维点云配准算法。首先提出了基于直径系数加权的圆孔骨骼识别算法,该算法引入向量夹角阈值实现直径特征系数加权,提取出圆孔骨骼点作为关键点;然后,基于圆心特征提出了新的描述符,在圆孔骨骼的中心构建了伪特征四边形,实现关键点的粗配准;接着,采用ICP算法对关键点进一步配准,并将得到的变换矩阵应用到圆孔局部上实现粗配准;最后,使用ICP算法实现圆孔局部的精配准。实验结果表明,与传统算法相比,配准误差降低1041以上,配准速度提高5422以上,且具有更强的鲁棒性。

    Abstract:

    To solve the problems of low accuracy and long time consumption in traditional descriptor algorithms for local registration of circular holes,a three dimensional point cloud registration algorithm for circular holes by means of constructing pseudo feature quadrilaterals is proposed.Firstly,a circular hole skeleton recognition algorithm based on diameter coefficient weighting is proposed,which introduces a vector angle threshold to achieve diameter feature coefficient weighting and extracts the circular hole skeleton points as key points.Then,a new descriptor is proposed based on the center feature,and a pseudo feature quadrilateral is constructed at the center of the circular hole to achieve rough registration of key points.Next,the ICP algorithm is used to further register the key points,and the obtained transformation matrix is applied to the local circular hole for coarse registration.Finally,ICP is used to achieve precise registration of local circular holes.The experimental results show that the registration error is reduced by more than 10.41% and the registration speed is improved by more than 54.22% with stronger robustness than the traditional algorithm.

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王一 ,姚永康,付智超,程佳.基于伪特征四边形的三维点云配准算法[J].激光与红外,2025,55(3):359~367
WANG Yi, YAO Yong-kang, FU Zhi-chao, CHENG Jia.3D point cloud registration algorithm based on pseudo feature quadrilateral[J]. LASER & INFRARED,2025,55(3):359~367

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  • 在线发布日期: 2025-03-14
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