A generalised feature for low level vision

• URL: http://arxiv.org/abs/2102.02000v1
• Date: Wed, 3 Feb 2021 11:02:03 GMT
• Title: A generalised feature for low level vision
• Authors: Dr David Sinclair and Dr Christopher Town
• Abstract summary: The Sinclair-Town transform subsumes the rolls of both edge-detector, MSER style region detector and corner detector. The difference from the local mean is quantised to 3 values (dark-neutral-light)
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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