摘要
传统的相机标定方法通常需要建立复杂3维标定块或高精度3维控制场,在实际应用中受到了一定的限制。本文采用平面控制格网作为标定块,根据相机的理想模型确定内方位元素,利用2维直接线性变换和共线方程分解出相机的外方位元素初值,采用改进的Hough变换算法检测标定图像中的格网直线并利用最小二乘法拟合出最佳直线,通过求直线的交点得到标定格网点的像坐标。最后利用自检校光线束法平差进行相机的精确标定。实际图像数据实验结果表明,主点和焦距的标定精度分别达到了0.2像素和0.3像素左右。可以满足高精度近景3维量测的要求。
Traditional camera calibration method usually need make complicated 3D calibration block or construct 3D control fields with high precision. In order to avoid this tedious work, we proposed a camera calibration method using planar control grid. First, camera＇ s initial values of intrinsic parameters are determined base on the perfect camera model and its extrinsic parameters using a 2D direct linear transformation and collinearity equations. Image coordinates of planar grid control points are detected using an improved Hough transformation algorithm and least squares fitting. Finally, camera calibration with high accuracy is conducted using bundle adjustment with self-calibration. Good results have been obtained with real image data calibration and demonstrate the method we proposed in this paper is feasible. Calibration precision of principle point and focal length is about 0. 2 and 0.3 pixels respectively, which can meet the precision requirements of close-range photogrammetry with high accuracy.
出处
《中国图象图形学报》
CSCD
北大核心
2007年第4期613-617,共5页
Journal of Image and Graphics
基金
中国矿业大学青年科研基金项目（2005A030）的资助
关键词
直接线性变换
共线方程
自检校光线束法平差
改进HOUGH变换
direct linear transformation, collinearity equation, bundle adjustment with self-calibration, improved Hough transformation
