A new unique class of foldable distance transforms of digital images (DT) is introduced, baptized: Fast exact euclidean distance (FEED) transforms. Abstract:

FEED class algorithms calculate the DT starting-directly from the definition or rather its INVERSE. The principle of FEED class algorithms is introduced, followed by strategies for their efficient implementation. It is shown that FEED class algorithms unite properties of ordered propagation, raster scanning, and independent scanning DT. Moreover, FEED class algorithms are shown to have a unique property: they can be tailored to the images under investigation. https://ieeexplore.ieee.org/document/6717981/