A new distance mapping and its use for shape measurement on binary patterns

Abstract

The paper describes a new class of distance mappings for binary images, which are based on a border-to-border distance rather than on the distance between an individual point and the border of an object. It is shown how these mappings can be used to calculate efficiently meaningful features like the "line-shapeness" or "compactness" of objects within binary images or to characterize binary images in a global sense. The algorithms involved are well suited for conventional sequential processors. © 1983.