  When using images to locate objects, there is the problem of correcting for
distortion and misalignment in the images. An elegant way of solving this
problem is to generate an error correcting function that maps points in an
image to their corrected locations. We generate such a function by fitting a
polynomial to a set of sample points. The objective is to identify a polynomial
that passes "sufficiently close" to these points with "good" approximation of
intermediate points. In the past, it has been difficult to achieve good global
polynomial approximation using only sample points. We report on the development
of a global polynomial approximation algorithm for solving this problem. Key
Words: Polynomial approximation, interpolation, image rectification.
