Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.281862
Title: Real-time optical intensity correlation using photorefractive BSO
Author: Wang, Zhao Qi
ISNI:       0000 0001 3562 4575
Awarding Body: University of Abertay Dundee
Current Institution: Abertay University
Date of Award: 1995
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Abstract:
Real-time optical intensity correlation using a photorefractive BSO crystal and a liquid crystal television is implemented. The underlying physics basis is considered, some specific techniques to improve the operation are proposed, and several optical pattern recognition tasks are achieved. Photorefractive BSO is used as the holographic recording medium in the real-time intensity correlator. To improve the dynamic holographic recording, a moving grating technique is adopted. The nonlinear effects of moving gratings at large fringe modulation are experimentally investigated, and are compared with numerical predictions. Optical bias is adopted to overcome the difficulty of a large drop in the optimum fringe velocity with moving gratings. The effects of optical bias on the optimum fringe velocity and on the diffraction efficiency are studied. To overcome the inherent drawback of low discrimination of intensity correlation in optical pattern recognition, real-time edge-enhanced intensity correlation is achieved by means of nonlinear holographic recording in BSO. Real-time colour object recognition is achieved by using a commercially available and inexpensive colour liquid crystal television in the intensity correlator. Multi-class object recognition is achieved with a synthetic discriminant function filter displayed by the Epson liquid crystal display in the real-time intensity correlator. The phase and intensity modulation properties of the Epson liquid crystal display are studied. A further research topic which uses the Epson liquid crystal display to realize a newly designed spatial filter, the quantized amplitude-compensated matched filter, is proposed. The performance merits of the filter are investigated by means of computer simulations.
Supervisor: Cartwright, Colin ; Gillespie, Allan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.281862  DOI: Not available
Keywords: Object recognition; Spatial filters
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