基于同心圆合成图像匹配的双目视觉标定

分析了双目视觉传感器的数学模型,提出了一种基于同心圆合成图像匹配的双目视觉传感器的标定方法。在测量范围内任意多次摆放同心圆靶标,由两台摄像机拍摄靶标图像。根据摄像机模型与已知同心圆在靶标坐标系上的位置关系,构造合成图像,将合成图像与观测图像进行相似度匹配,通过优化定位得到靶标上每个圆的圆心点图像坐标。利用左右图像对应的圆心图像坐标和双目视觉的约束关系,对双目视觉传感器参数进行非线性优化,并得到最优解。所提出的标定方法是在张正友方法的理论基础上,利用了图像的整体性进行的优化。实验结果表明,该方法提高了标定精度。

Calibration Method for Binocular Vision Based on Matching Synthetic Images of Concentric Circles

The mathematical model of a binocular vision sensor is analyzed. A novel calibration method for binocular vision sensor based on matching the synthetic images of concentric circles is proposed. The target of concentric circles is randomly placed in the field of vision sensor for several times and the images of target are acquired by two cameras. The synthetic images are calculated through the model of camera and the known position of concentric circles in the target plane. By matching the synthetic images and observed images, the coordinate of the centre circles in image plane is located with optimization. Then, based on the image coordinate of the concentric circles in two cameras and the constraint of binocular vision, the parameters of binocular vision sensor are optimized by Levenberg-Marquart method. Based on the calibration proposed by Z.Y.Zhang, the whole information of the images is optimized. The experiment shows that the accuracy of calibration is improved.