= Checkerboard calibration target
A <checkerboard calibration target> is a planar pattern of alternating dark and light squares with known geometry, used to estimate <camera calibration> parameters. Image measurements of internal corner intersections are paired with known target coordinates. Several tilted views constrain the image projection and distortion model.<Camera Calibration in the OpenCV-Python tutorials>[Code, known checkerboard points, corner detection and calibration]{ref}
For a board with nine squares across and six down, the internal-corner grid has eight columns and five rows. If square spacing is 20 millimetres, one can assign corner coordinates $(20i,20j,0)$ millimetres for $i=0,\ldots,7$ and $j=0,\ldots,4$. Supplying only unit grid spacing instead yields translation estimates in square-size units. A useful experiment varies the target's orientation and image position, then examines <reprojection error>. Repeated identical views provide less geometric information; a warped board or inaccurate corner measurements can also bias the fitted camera model.
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