Fast Exact Euclidean Distance (FEED) Transformation

Authors:
Theo Schouten;Egon van den Broek
Affiliations:
University of Nijmegen, The Netherlands;University of Nijmegen, The Netherlands
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Year:
2004

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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.