基于Hough变换和圆形模板的棋盘格角点检测

Checkerboard Corner Detection Based on Hough Transform and Circular Template

针对现有棋盘格角点检测算法存在精度不足的问题,提出一种基于Hough变换和圆形模板的高精度棋盘格角点检测算法:首先,利用Hough变换和棋盘格直线分布特征获取有效直线,构建棋盘格角点,实现角点的粗略定位;其次,构建圆形模板,使其在粗略定位的角点周围移动,搜索相关点并获取其图像坐标及其观测距离;最后,最小化多个相关点坐标的实际距离与其观测距离的差值并求解,实现角点的精确定位。实验结果表明,本文提出的棋盘格角点方法与现有方法相比,其标定误差明显减少;在光照不理想时,本文方法可以实现精确检测。该方法为实际摄像机高精度标定应用提供了有力依据。

Aiming at resolving the issue of accuracy of the existing checkerboard corner detection algorithms,we propose a high-precision checkerboard corner detection algorithm based on Hough transform and circular template.First,we used the Hough transform to extract straight lines in an image,used the distribution features of the checkerboard lines to obtain the effective straight lines,and then obtained and roughly located the approximate corner points based on these lines.Second,we constructed a new circular template that is moved around the roughly located corner points to search for related points;we simultaneously obtained their image coordinates and observation distances.Finally,we solved more accurate corners,which should satisfy the minimum difference between the actual distances from related points and their observation distances.The experimental results reveal that the calibration error of the proposed method significantly reduces compared with the existing methods.When the illumination is not ideal,the proposed method can also realize accurate detection.This method provides a strong basis for the application of high-precision calibration of actual cameras.