Abstract

A method has been developed for recognizing the shape of a surface from the intensity and polarization of reflected radiation. The recognition is carried out when the character of the surface illumination is known. The variations of the intensity and polarization of the radiation on a reference object are determined as a function of the geometry of the reflecting surface, and then the resulting data make it possible to reconstruct the shape of arbitrary surfaces. These computations are carried out on a cellular neural network by means of an optimization method based on the principle of evolution to the global minimum of the energy function.

© 2008 Optical Society of America

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