Abstract
Various techniques have been employed to recover three-dimensional (3D) surfaces in the redesign of products, customized designs, and the building of virtual environments. Reverse engineering methodology provides an efficient tool for the manufacturing of free-form and sculptured shapes. This paper describes an image processing approach to the 3D shape recovery based on neural networks that tackles the major bottleneck in the current reverse engineering process, namely the lack of a rapid link between the physical object and its design representation. A range of applications has shown this method to be feasible and efficient.
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