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Eigenvector decomposition of a multiresolution operator

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Wong, June and Wilson, Roland (1990) Eigenvector decomposition of a multiresolution operator. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)

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Abstract

Pattern recognition using a multiresolution representation was investigated. This was addressed as an eigenvalue problem. Eigenvector decomposition of a multiresolution operator enabled a low-pass pyramid representation to be expressed in terms of the 'eignpatterns' of the operator. The findings show that different image features 'emerge' and can be recognised at different levels of the multiresolution structure, i.e. at different resolutions. The level depends on the feature size. This work has implications in the design of a neural network for pattern recognition, namely that a network could 'learn' the eigenpattern of a multiresolution operator. Patterns recognition processing could proceed in a top-down, hierarchical manner, beginning at a level of coarse features and using information from lower levels in the multiresolution structure to guide the processing of finer detail.

Item Type: Report
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Pattern recognition systems, Eigenvectors
Series Name: Department of Computer Science research report
Publisher: University of Warwick. Department of Computer Science
Official Date: September 1990
Dates:
DateEvent
September 1990Completion
Number: Number 167
Number of Pages: 34
DOI: CS-RR-167
Institution: University of Warwick
Theses Department: Department of Computer Science
Status: Not Peer Reviewed
Publication Status: Unpublished
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