一种基于棋盘格的高精度分区域相机标定方法

在视觉测量系统中，相机的标定精度至关重要，将影响整个测量系统的精度。针对现有相机标定方法难以兼顾精度和操作复杂度的问题，本文提出了一种基于棋盘格的高精度分区域相机标定方法。首先，将棋盘格置于不同位置，提取不同位置角点的世界坐标和像素坐标，对所有角点用线性变换和非线性最优算法求解出全局标定参数。然后，将角点分为中间区域角点和边缘区域角点，对两区域角点分别标定得到两组分区域标定参数。标定实验结果表明：与全局标定法相比，分区域标定法的图像平均投影误差至少降低16%。该方法操作简单，精度高，可以很好的应用于工业视觉检测。

A new technique for high precision sub-regional camera calibration based on checkerboard pattern

Camera calibration is critical in computer vision measurement system,affecting the accuracy of the whole system. Many camera calibration methods have been proposed,but they cannot consider precision and operation complexity at the same time.In this paper,a new technique is proposed to calibrate camera.Firstly,the global calibration method is described in de-tail.It requires the camera to observe a checkerboard pattern shown at a few different orientations.The checkerboard corners are obtained by Harris algorithm.With direct linear transformation and non-linear optimal algorithm,the global calibration pa-rameters are obtained.Then,a sub-regional method is proposed.Those corners are divided into two groups,middle corners and edge corners,which are used to calibrate the corresponding area to get two sets of calibration parameters.Finally,some experimental images are used to test the proposed method.Experimental results demonstrate that the average projection error of sub-region method is decreased at least 1 6% compared with the global calibration method.The proposed technique is simple and accurate.It is suitable for the industrial computer vision measurement.