A connectionist classifier architecture applied to image segmentation

Abstract

A connectionist classifier architecture that is used in an image segmentation scheme based upon a decision analysis paradigm is described. An appropriate architecture for a connectionist classifier is discussed, and its relationship to other image segmentation architectures following the same paradigm is shown. The performance of a complete system, including pixel descriptor extraction and connectionist classifier, is demonstrated using scenes from industrial inspection and combustion chamber research tasks.<>