Distance maps from unthresholded magnitudes

Authors:
Luis Anton-Canalis;Mario Hernandez-Tejera;Elena Sanchez-Nielsen
Affiliations:
SIANI, University of Las Palmas de Gran Canaria;SIANI, University of Las Palmas de Gran Canaria;University of La Laguna
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

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Abstract

A straightforward algorithm that computes distance maps from unthresholded magnitude values is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of segmented images using the watershed algorithm and the measurement of pixel value stability in video sequences.