  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.
