一种新的短边校正线性边缘拟合方法

Fujun Wang, Xuteng Qin, Zhichen Huo, Dawei Zhang
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引用次数: 0

摘要

本文提出了一种新的微视觉线性拟合方法,可用于精确估计微装配中部件的位姿。通过Canny边缘检测获取边缘信息后,提出改进的最小二乘法对小分量的线性边缘进行拟合,利用阈值降低点集中异常值的影响。为了提高估计精度,利用检测到的折线信息对拟合的线性边缘进行迭代校正。与传统的线性边缘拟合方法相比,实验结果表明,该方法可以有效地减小拟合线的置信区间,有助于提高微装配中姿态估计的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Linear Edge Fitting Method with Short Edge Correction
In this paper, a novel linear fitting method for micro vision is proposed, which can be utilized to accurately estimate the pose of components in micro-assembly. After obtaining the edge information through Canny edge detection, an improved least square method is put forward to fit the linear edge of small components, where a threshold is utilized to reduce the influence of outliers in point set. In order to improve the estimation accuracy, the fitted linear edge is iteratively corrected through the information of detected broken lines. Compared with conventional linear edge fitting methods, the experimental results indicated that proposed method could effectively reduce the confidence interval of the fitted line, which would be helpful to improve the accuracy of pose estimation in micro-assembly.
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