面向复杂环境的圆形标志高精度定位方法

标志定位精度影响着视觉测量的精度，针对复杂环境测量标志自动定位精度不高的问题，本文提出一种基于亚像素弧段法的圆形标志中心定位方法。该方法首先对预处理图像进行边缘检测与跟踪，提取亚像素边缘序列，再利用边缘显著点与弧段几何特性对边缘序列进行中心约束，有效剔除伪圆弧特征，然后用更高效的相对位置约束与内接三角形约束对边缘弧段进行重组，最后对弧段组进行最小二乘拟合实现标志中心精确定位。本文通过提取亚像素弧段序列与更高效的弧段重组方法，提高了定位精度的同时，减少了弧段重组的时间。实验表明，在模拟图像的定位精度达到0.007 pixel,动态位移实验中精度达到0.05 mm,在光照变化、噪声、遮挡等不良条件下均能够满足视觉测量实时定位的需求。

High-precision positioning method for circular target in complex background

A high-precision positioning method was proposed to meet the demands for automatic positioning in complex backgrounds. First, sub-pixel edge sequences are derived from discrete edge points of a preprocessed image by applying an edge tracing algorithm and interpolation algorithm. Next, the non-circular edges were excluded by salient point segmentation and center constraints based on geometric features. Then arcs belonging to the same circle are reorganized by more efficient relative position constraints and inscribed triangle constraints. And finally the arc segment group was subjected to least squares fitting to achieve accurate positioning of the target center. In this paper, by extracting sub-pixel arc sequence and a more efficient arc recombination method, the positioning accuracy is improved and the time of arc recombination is reduced. The experimental results demonstrate that the positioning accuracy of the simulated image reaches 0.007 pixel, and the accuracy of the dynamic displacement experiment reaches 0.05 mm, which can meet the needs of visual measurement real-time positioning under adverse conditions such as illumination changes, noise, and occlusion.