<title>Genetic algorithms in hypothesize-and-verify image interpretation</title>

Abstract

Image interpretation plays an important role in computer vision and robotics. We describe here a new approach to image understanding whose novel feature is that it integrates segmentation and interpretation into a single feedback process that incorporates contextual knowledge and uses a genetic algorithm technique to produce an optimal image interpretation. In this paper, we describe the principles of our approach, demonstrate its feasibility, and assess the accuracy of the proposed method using artificially-generated images.