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,
the only error is the zero-mean independent and identically distributed
random 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.
The camera calibration toolbox for Matlab (version 3.0) utilizes a new bias correction procedure for circular control points and a nonrecursive method for reversing the distortion model. To learn more about the calibration method see [1].
The toolbox is freely available, and you can download it from here:
calibr_v30.tar
(103 k) or
calibr_v30.zip
(32 k)
Reference:
[1] Heikkilä, J, "Geometric Camera Calibration Using Circular Control Points", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, pp. 1066-1077, Oct 2000.