A REAL-TIME IMAGE SEGMENTATION SYSTEM USING A CONNECTIONIST CLASSIFIER ARCHITECTURE

Abstract

An image segmentation system which uses a connectionist classifier architecture as a central building block is described in this paper. The complete system, which consists of a feature extraction module and the connectionist classifier module, has been designed and implemented in digital VLSl; system architectural aspects as well as the procedure of adaptation of the system to different segmentation problems are discussed. The performance of the segmentation system on real world problems is demonstrated using scenes from industrial inspection, texture recognition, and combustion chamber research tasks.