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arXiv · 2102.02000

A generalised feature for low level vision

Dr David Sinclair·Dr Christopher Town
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Abstract

This papers presents a novel quantised transform (the Sinclair-Town or ST transform for short) that subsumes the rolls of both edge-detector, MSER style region detector and corner detector. The transform is similar to the $unsharp$ transform but the difference from the local mean is quantised to 3 values (dark-neutral-light). The transform naturally leads to the definition of an appropriate local scale. A range of methods for extracting shape features form the transformed image are presented. The generalized feature provides a robust basis for establishing correspondence between images. The transform readily admits more complicated kernel behaviour including multi-scale and asymmetric elements to prefer shorter scale or oriented local features.

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Dr David Sinclair, Dr Christopher Town. 2021-02-03. A generalised feature for low level vision. https://arxiv.org/abs/2102.02000

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