Abstract
M.Sc. (Computer Science)
This dissertation examines the field of computer vision, with special attention being given to
vision systems that support digitized video image analysis. The study may be broadly divided
into three main sections.
The first part offers an introduction to standard vision systems, focusing on the hardware
architectures and the image analysis techniques used on them. Hardware configurations
depend mainly on the selected frame-grabber and processor type. Parallel architectures are
highlighted, as they represent the most suitable platform for a real-time digitized video image
analysis system. The image analysis techniques discussed include: image preprocessing,
segmentation, edge detection, optical flow analysis and optical character recognition.
The second part of the study covers a number of real-world computer vision applications, and
commercially available development environments. Several traffic surveillance systems are
discussed in detail, as they relate to the practical vehicle identification system developed in the
third part of the study.
As mentioned above, the development of a Vehicle Identification Prototype, called VIP, forms
the basis for the third and final part of this study. The VIP hardware requirements are given,
and the software development and use is explained. The VIP's source code is provided so that
it may be evaluated, or modified, by any interested parties.