分析和讨论的结果为亚像素边缘定位技术的选取提供可靠依据。
The contrast result provided a reliable basis for selecting subpixel edge detections in practice.
利用亚像素边缘定位算法，对砂轮图像进行轮廓提取，并与理论轮廓进行比较。
The outline edge of grinding wheel can be extracted with the algorithm, and the detected result is compared with the perfect outline.
使用CCD成像的机器视觉系统进行精加工零件尺寸检测时，图像轮廓边缘的亚像素定位分析是决定测量精度的一个重要因素。
The subpixel localization is a key factor to determinate measurement accuracy in using CCD vision measurement system for measuring the size of precision part.
方法中采用基于类椭圆边缘属性对特征区域进行自动识别，采用最小二乘椭圆拟合精确求取类椭圆亚像素定位中心。
In the method, the automatic identification of feature area is fulfilled based on the edge attribute, and the sub-pixel center location is accomplished with the least-square approach.
因此，用于边缘精确定位的亚像素算法已被广泛研究。
Therefore, the sub-pixel algorithm in edge precise positioning was widely researched.
利用理想光条法，比较了几种有代表性的亚像素算法对于圆弧状边缘的定位能力。
Through ideal light bar method, some representative sub-pixel algorithm were compared for the capability of positioning circular arc edge.
构建了基于计算机视觉的齿形链链板的测量系统，对直线和圆的边缘定位，提出了新的亚像素算法，计算了齿形链链板的销孔直径及圆度误差、链板节距和两直边夹角，对测量结果进行了误差分析。
The measurement system on chain board of tooth shape chain was established based on computer vision, and a new kind of sub-pixel algorithm for edge orientation of beeline and circle was put forward.
实验结果表明：在低噪声图像中，两种算法的边缘定位精度均达到满意的结果，且最小二乘线性回归亚像素定位算法速度较快。
The experiment results show that the precision of two algorithms is satisfactory and the velocity of the MLS linear regression subpixel localization is faster.
为了提高微操作系统的装配精度，提出了一种新型的亚像素边缘检测和中心定位算法。
In order to improve the resolution and accuracy of micro-assembly systems, a novel sub-pixel edge detection and center localization algorithm for micro-parts is presented.
为了提高微操作系统的装配精度，提出了一种新型的亚像素边缘检测和中心定位算法。
In order to improve the resolution and accuracy of micro-assembly systems, a novel sub-pixel edge detection and center localization algorithm for micro-parts is presented.
应用推荐