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Title: A VLSI smart sensor-processor for fingerprint comparison
Author: Anderson, Stuart
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1993
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Image processing techniques are increasingly being applied to new applications beyond their traditional uses for remote sensing image data enhancement. These new areas, such as machine vision for automated production line monitoring and control and financial transaction security, require low-cost compact but highly reliable systems. This thesis discusses some of the problems in achieving this goal and presents a novel approach to the implementation of low-cost real-time image processing systems. The method presented in this thesis utilises the usual system design leverage offered by VLSI of reduced cost, power, size and weight; achieved as a result of the freedom to efficiently map algorithms to hardware. In addition, substantial further advantages are obtained by integrating the image sensor and preprocessing interface circuits onto the same silicon substrate. During the course of this work three custom integrated circuits for real-time image processing were designed, simulated, fabricated and tested. Two of the devices form the image processing core of an entirely new, working, fingerprint based access control system. These designs then led to the development of the third device and the main focus of this thesis, a highly integrated sensor-processor for fingerprint comparison. This device has applications in many fields where personal identification is vital such as physical access control, financial transaction and health care. The architecture can also be adapted to address more general pattern recognition tasks. It is shown that through the efficient integration of the sensing, processing and memory elements of the fingerprint comparison system, increased performance and greatly reduced manufacturing costs can be achieved.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available