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Proceedings Paper

Symmetry recognition in images
Author(s): Kumar Eswaran
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Paper Abstract

This paper is concerned with the problem of separation of data, by a neural based computer recognition system. To this end certain types of data which are `tricky' are studied in order to see if they can be separated (i.e. classified) by a neural network or by a Kohonen based classifier. It is shown that there exist data which cannot simply be separated by a nearest distance classifier and yet can be treated well by a neural network, these correspond to the symmetry problem in images. In this paper the question that is posed and answered is: `If we are given a set of binary images, is it possible to devise an algorithm which will enable the computer to automatically recognize those images which have an inherent symmetry or near-symmetry?' It is demonstrated that a neural based algorithm can be trained to do the job efficaciously.

Paper Details

Date Published: 19 July 1999
PDF: 2 pages
Proc. SPIE 3749, 18th Congress of the International Commission for Optics, (19 July 1999); doi: 10.1117/12.354993
Show Author Affiliations
Kumar Eswaran, Bharat Heavy Electricals Ltd. (India)

Published in SPIE Proceedings Vol. 3749:
18th Congress of the International Commission for Optics
Alexander J. Glass; Joseph W. Goodman; Milton Chang; Arthur H. Guenther; Toshimitsu Asakura, Editor(s)

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