A generalised feature for low level vision

02/03/2021 ∙ by Dr David Sinclair, et al. ∙ 13

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.



There are no comments yet.


page 3

page 4

page 6

page 7

page 9

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.