Geometric camera calibration using circular control points

Modern CCD cameras are usually capable of a spatial accuracy greater than 1 /50 of the pixel size. However, such accuracy is not easily attained due to various error sources that can affect the image formation process. Current calibration methods typically assume that the observations are unbiased, t he only error is the zero-mean independent and identically distributed rand om noise in the observed image coordinates, and the camera model completely explains the mapping between the 3D coordinates and the image coordinates. in general, these conditions are not met, causing the calibration results to be less accurate than expected. In this paper, a calibration procedure f or precise 3D computer vision applications is described. It introduces bias correction for circular control points and a nonrecursive method for rever sing the distortion model. The accuracy analysis is presented and the error sources that can reduce the theoretical accuracy are discussed. The tests with synthetic images indicate improvements in the calibration results in l imited error conditions. In real images, the suppression of external error sources becomes a prerequisite for successful calibration.