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On Using Physical Analogies for Feature and Shape Extraction in Computer Vision
Mark S. Nixon , Xin U. Liu , Cem Direkoğlu , David J. Hurley
September 2008
Visions of Computer Science - BCS International Academic Conference (VOCS)
BCS International Academic Conference
22 - 24 September 2008
Feature extraction, Shape detection, Image processing, Computer vision, Force field, Water flow, Heat
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Abstract
There is a rich literature of approaches to image feature extraction in computer vision. Many sophisticated approaches exist for low- and high-level feature extraction but can be complex to implement with parameter choice guided by experimentation, but impeded by speed of computation. We have developed new ways to extract features based on notional use of physical paradigms, with parameterisation that is more familiar to a scientifically-trained user, aiming to make best use of computational resource. We describe how analogies based on gravitational force can be used for low-level analysis, whilst analogies of water flow and heat can be deployed to achieve high-level smooth shape detection. These new approaches to arbitrary shape extraction are compared with standard state-of-art approaches by curve evolution. There is no comparator operator to our use of gravitational force. 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.
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