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In this paper we report on the development of a global function approximation algorithm for image rectification and registration. The approximation algorithm fits a linear combination of two-dimensional Chebyshev polynomials to a set of sample points obtained from a test image. The algorithm was successfully used to map pixel positions in unrectified images to object locations on a planar surface. The mapping was used to guide a robot arm to objects placed on the surface, thus demonstrating the practical utility of the algorithm.