一种棋盘格靶标不完整角点识别的修正算法

A Modified Algorithm for Incomplete Corner Identification of Chess Board Target

针对Hessian算子在棋盘格角点检测过程中边缘局部区域角点检测失败的问题,提出一种恢复角点识别的修正算法.首先基于坐标极值法自动识别棋盘格极点及边缘包络点,提取可以完整检测到所有包络点的2条边缘线上各自首尾及中间3个特征角点;然后利用交比不变原理求出边缘线上的消失点,并依据消失点原理求出未检测到的极点;最后根据四极点图像坐标与世界坐标的单应性关系重投影得出所有角点坐标.实验结果表明,与常用棋盘格角点检测算法相比,该算法具有较强的鲁棒性,处理过程可自动实现,在摄像机标定的应用上具有较高的实用价值.

For the problem of local edge corner failure detection by Hessian operator in the process of the chess board corner detection, a new modified algorithm is proposed to recover the corner recognition. In this algorithm, firstly, based on coordinate extremes method, the chess board poles and the envelope corners on the edge was identified automatically, and the three feature points of head, tail and middle corners on two edge lines were extracted, on which all envelope corners can be detected. After that, the vanishing points of the edge lines were obtained by the use of cross ratio invariance, thus the no-detected pole can be calculated according to the principle of vanishing point. Finally, all the corner coordinates were obtained by the reprojection from the homography relationship between the image coordinates and the world coordinates of the four poles. The experimental results show that this method has strong robustness and can be realized automatically with compared to the common detection methods, so it is of great practical value for camera calibration.