Spiral architecture for machine vision

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dc.contributor Sheridan, Phillip en_AU
dc.date.accessioned 2007-03-14T01:52:56Z
dc.date.accessioned 2012-12-15T03:51:52Z
dc.date.available 2007-03-14T01:52:56Z
dc.date.available 2012-12-15T03:51:52Z
dc.date.issued 1996
dc.identifier.uri http://hdl.handle.net/2100/280
dc.identifier.uri http://hdl.handle.net/10453/20059
dc.description University of Technology, Sydney. School of Computing Sciences. en_AU
dc.description.abstract This thesis presents a new and powerful approach to the development of a general purpose machine vision system. The approach is inspired from anatomical considerations of the primate's vision system. The geometrical arrangement of cones on a primate's retina can be described in terms of a hexagonal grid. The importance of the hexagonal grid is that it possesses special computational features that are pertinent to the vision process. The fundamental thrust of this thesis emanates from the observation that this hexagonal grid can be described in terms of the mathematical object known as a Euclidean ring. The Euclidean ring is employed to generate an algebra of linear transformations which are appropriate for the processing of multidimensional vision data. A parallel autonomous segmentation algorithm for multidimensional vision data is described. The algebra and segmentation algorithm are implemented on a network of transputers. The implementation is discussed in the context of the outline of a general purpose machine vision system's design. en_AU
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dc.language en en_AU
dc.language.iso en_AU
dc.rights http://www.lib.uts.edu.au/disclaimer.html en_AU
dc.rights Copyright Phillip Sheridan en_AU
dc.subject Computer vision. en_AU
dc.subject Pattern recognition. en_AU
dc.title Spiral architecture for machine vision en_AU
dc.type Thesis (PhD)


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