Formulation of a set of rules for deriving optimal low-level image feature detection masks

This paper studies the problem of designing optimal templates for detecting variable signals which appear on a varying baseline. A mathematical analysis based on the matched filter concept shows that templates must be adjusted towards zero mean, with weights which take account of mask region areas and associated signal variability parameters. In addition, a new equal area rule is derived and applied to the corner detection problem.