Hodge, Victoria, O'Keefe, Simon and Austin, Jim (2006) A Binary Neural Shape Matcher using Johnson Counters and Chain Codes. In: BICS :. Brain Inspired Cognitive Systems 2006, 2006-10-10 - 2006-10-14, Island of Lesvos. .
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Abstract
In this paper, we introduce a neural network-based shape matching algorithm that uses Johnson Counter codes coupled with chain codes. Shape matching is a fundamental requirement in content-based image retrieval systems. Chain codes describe shapes using sequences of numbers. They are simple and flexible. We couple this power with the efficiency and flexibility of a binary associative-memory neural network. We focus on the implementation details of the algorithm when it is constructed using the neural network. We demonstrate how the binary associative-memory neural network can index and match chain codes where the chain code elements are represented by Johnson codes.
| Item Type: | Proceedings Paper |
|---|---|
| Copyright, Publisher and Additional Information: | See also http://eprints.whiterose.ac.uk/5431/ |
| Keywords: | Neural, Associative Memory, Shape Matcher, BinaryEncoding |
| Academic Units: | The University of York > Computer Science (York) |
| Depositing User: | Dr Victoria Hodge |
| Date Deposited: | 08 Sep 2008 15:28 |
| Last Modified: | 19 Feb 2013 15:21 |
| Status: | Published |
| Refereed: | No |
| URI: | http://eprints.whiterose.ac.uk/id/eprint/4619 |
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