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The Computer Journal Advance Access published online on August 7, 2009
The Computer Journal, doi:10.1093/comjnl/bxp070
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© The Author 2009. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

On Using Physical Analogies for Feature and Shape Extraction in Computer Vision

Mark S. Nixon*, Xin U. Liu, Cem Direkoglu and David J. Hurley

School of Electronics and Computer Science, University of Southampton, Southampton SO17 1ST, UK

* Corresponding author: msn{at}ecs.soton.ac.uk

Received 27 October 2008; revised 22 May 2009

There is a rich literature of approaches to image feature extraction in computer vision. Many sophisticated approaches exist for low- and for high-level feature extraction but can be complex to implement with parameter choice guided by experimentation, but with performance analysis and optimization impeded by speed of computation. We have developed new feature extraction techniques on notional use of physical paradigms, with parametrization aimed to be more familiar to a scientifically trained user, aiming to make best use of computational resource. This paper is the first unified description of these new approaches, outlining the basis and results that can be achieved. We describe how gravitational force can be used for low-level analysis, while analogies of water flow and heat can be deployed to achieve high-level smooth shape detection, by determining features and shapes in a selection of images, comparing results with those by stock approaches from the literature. We also aim to show that the implementation is consistent with the original motivations for these techniques and so contend that the exploration of physical paradigms offers a promising new avenue for new approaches to feature extraction in computer vision.

Key Words: feature extraction • shape detection • image processing • computer vision • force field • water flow • heat

Handling editor: Ethem Alpaydin


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