摘要
三角网格模型配准是工业自动化检测软件中的重要一环,其配准精度对检测机械零件的形位公差有重要影响。针对三角网格模型的自动配准精度低、鲁棒性差的问题,本文提出一种面向机械零件三角网格模型自动配准中增强特征的分割方法。首先,确定三角网格模型特征分割的K值,通过拉普拉斯矩阵确定种子点进行迭代初始化。其次,本文采用合适的区域形状代理和代价函数以加速该过程,并通过多源迭代聚类得到特征分割结果。最终,在三角网格模型特征分割结果的基础上进行基于奇异值分解法的粗配准,之后再根据EM-ICP进行精配准。与传统的特征描述子粗配准结合ICP精配准的方法进行对比,结果表明,本文方法的配准误差下降了25.2%,自动配准时间缩短了62.6%,有效地提高了三角网格模型自动配准的精度和效率。
Triangular mesh model registration is an important part of industrial automation detection software.The registration accuracy has an important influence on mechanical parts'shape and position tolerance.Aiming to solve the problems of low accuracy and poor robustness of the automatic registration of triangular mesh models,we propose a segmentation method for enhanced features in the automatic registration of triangular mesh models for mechanical parts.First,the K value of the feature segmentation of the triangular mesh model was determined,and the Laplacian matrix determined the seed points for iterative initialization.Second,the appropriate region shape agent and cost function were used to accelerate the process and perform multi-source iterative clustering to obtain the intended feature segmentation results.Finally,based on the feature segmentation results of the triangular mesh model,the coarse registration based on the singular value decomposition method was performed,then the fine registration was performed according to the EMICP.The experimental results show that the proposed method reduces registration error by 25.2% and shortens the automatic registration time by 62.6%,compared with the traditional feature descriptor coarse registration combined with ICP fine registration method.This effectively improves the accuracy and efficiency of the automatic registration of the triangular mesh model.
作者
巫志辉
王立忠
梁晋
龚春园
朱峰
常志文
徐建宁
WU Zhi-hui;WANG Li-zhong;LIANG Jin;GONG Chun-yuan;ZHU Feng;CHANG Zhi-wen;XÜJian-ning(State Key Laboratory for Manufacturing Systems Engineering,College of Mechanical Engineering,Xi’an Jiaotong University,Xi’an 710049,China)
出处
《中国光学（中英文）》
EI
CAS
CSCD
北大核心
2024年第5期1112-1124,共13页
Chinese Optics
基金
国家重点研发计划项目(No.2022YFB4601802)
国家自然科学基金资助项目(No.52275543)。
关键词
三角网格模型
特征分割
种子点选取
分割后处理
自动配准
triangular mesh model
feature segmentation
seed point selection
segmentation post-processing
automatic registration
