Generating Distance Maps with Neighbourhood Sequences
A sequential algorithm for computing the distance map using distances based on neighbourhood sequences (of any length) in the 2D square grid; and 3D cubic, face-centered cubic, and body-centered cubic grids is presented. Conditions for the algorithm to produce correct results are derived using a path-based approach. Previous sequential algorithms for this task have been based on algorithms that compute the digital Euclidean distance transform. It is shown that the latter approach is not well-suited for distances based on neighbourhood sequences.
KeywordsShort Path Grid Point Weighted Distance Image Domain Sequential Algorithm
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- 4.Fouard, C., Strand, R., Borgefors, G.: Weighted distance transforms generalized to modules and their computation on point lattices. Technical report, Centre for Image Analysis, Uppsala University, Uppsala, Sweden (Internal report 38) (2006)Google Scholar
- 10.Danielsson, P.E.: Minimal error octagonal metric in two and three dimensions. Internal report LiTH-ISY-1-1382, Linköping University, Linköping, Sweden (1992)Google Scholar
- 16.Carvalho, B.M., Garduño, E., Herman, G.T.: Multiseeded fuzzy segmentation on the face centered cubic grid. In: Singh, S., Murshed, N., Kropatsch, W.G. (eds.) ICAPR 2001. LNCS, vol. 2013, p. 339. Springer, Heidelberg (2001)Google Scholar
- 19.Strand, R., Nagy, B.: Some properties for distances based on neighbourhood sequences in the face-centered cubic grid and the body-centered cubic grid. Technical report, Centre for Image Analysis, Uppsala University, Uppsala, Sweden (Internal Report 39) (2006)Google Scholar