Application Of Binary Phase-Only Correlation To Machine Vision

Abstract

An experimental coherent optical correlator implementing real-time binary phase-only filters (BPOFs) and a matching computer model that simulates and predicts correlator performance are used to investigate target recognition and location and character recognition for images of interest in industrial applications. Good quantitative agreement between the computer model and the experiment is exhibited over hundreds of correlation pairs. Rotation and scale sensitivities are measured, and three types of composite smart filter are applied to reduce these sensitivities while maintaining good clutter object rejection. The effect of edge enhancing the subject images is investigated. Simple and composite BPOFs also demonstrate promising character recognition performance. The performance of magneto-optic spatial light modulators implementing BPOFs is validated, as is the use of computer simulations to predict performance. The potential of hybrid adaptive correlators based on this approach for industrial machine vision applications is demonstrated.