A comparative study of nonlinear shape models for digital image processing and pattern recognition

Four nonlinear shape models are presented: polynomial, Coons, perspective, and projective modes. Algorithms and some properties of these models are provided. For a given physical model, such as a perspective model, comparisons are made with other mathematical models. It is proved that, under certain conditions, the perspective models can be replaced by the Coons models. Problems related to substitution and approximation of practical models that facilitate digital image processing are raised and discussed. Experimental results on digital images are presented