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.