A hybrid computer architecture for machine vision

Abstract
A hybrid computer architecture for machine vision which combines the useful properties of different types of architectures is introduced. HYBRID, an experimental hybrid system consisting of specialized Datacube-compatible processors and a transputer network, has been developed in a Sun-3 environment. The VLSI implementation of an edge-preserving smoothing operator for the low-level vision system is described, and the performance of transputer-based systems for higher-level vision is evaluated. Methods for analyzing and optimizing the performance of a hybrid architecture are discussed.

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