基于鱼眼相机混合模型的棋盘格角点检测方法

Chessboard corner detection method based on fisheye camera hybrid model

针对搭载自动泊车功能车辆的鱼眼相机标定耗时较长、鲁棒性要求较高的问题,提出一种基于鱼眼相机混合模型的棋盘格内角点检测改进方法。在参考和比较原有算法的基础上,提出的混合畸变模型能够快速确定不同区域内角点的两个初始方向,从而快速提高粗定位的速度。同时针对生产线标定的特殊性,提出了双标准离率差阈值作为对初始棋盘格是否可用的判断标准。实验结果表明该算法在自动泊车鱼眼相机生产过程中既能够满足标定的精度要求,同时也大幅度提高了检测速度,对自动泊车的相机标定具有一定的实用价值。

In order to solve the problem that the calibration of fisheye camera with automatic parking vehicle is time-consuming,an improved chessboard corner detection method based on growth is proposed in this paper.On the basis of the original algorithm,the proposed hybrid distortion model can quickly determine the two initial directions of corners in different regions,so as to quickly improve the speed of rough positioning.At the same time,according to the particularity of production line calibration,the threshold of double standard deviation is proposed as the criterion to judge the initial chessboard.The experimental results in the production line environment show that the algorithm can not only meet the accuracy requirements of calibration,but also greatly improve the detection speed,and has a certain practical value for the calibration of production line camera.