Abstract
Fast exact Euclidean distance (FEED) transformation is introduced, starting from the inverse of the distance transformation. The prohibitive computational cost of a naive implementation of traditional Euclidean distance transformation is tackled by three operations: restriction of both the number of object pixels and the number of background pixels taken in consideration and pre-computation of the Euclidean distance. Compared to the Shih and Liu 4-scan method the FEED algorithm is often faster and is less memory consuming.
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