抄録
With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. In this paper, we present an algorithm for camera calibration using perspective ratio of a grid type frame with different line widths. It can easily estimate camera calibration parameters such as focal length, scale factor, pose, orientations, and distance. But, radial lens distortion is not modeled. The advantage of this algorithm is that it can estimate the distance of the object. To validate proposed method, we set experiments with a frame on rotator at a distance of 1.2[m] from camera and rotate the frame from -60 to 60 degrees. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. The average scale factor tends to fluctuate with small variation and makes distance error decrease. Compared with classical methods that use stereo camera or two or three orthogonal planes, the proposed method is easy to use and flexible. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use
