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. © 2011 Springer-Verlag.
CITATION STYLE
Anton-Canalis, L., Hernandez-Tejera, M., & Sanchez-Nielsen, E. (2011). Distance maps from unthresholded magnitudes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6669 LNCS, pp. 92–99). https://doi.org/10.1007/978-3-642-21257-4_12
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