Abstract
The distance transformation (DT) is a basic operation in image analysis where it is used for object recognition. A DT converts a binary image consisting of foreground pixels and background pixels, into an image where all background pixels have a value equal to the distance to the nearest foreground pixel.
We present several approaches for the parallel calculation of the distance transform based on the “divide-and-conquer” principle. The algorithms and their performance on an iPSC®/2 are discussed for the city block (CB) distance that is an approximation for the Euclidean Distance.
The following text presents research results of the Belgian Incentive Program “Information Technology” — Computer Science of the future, initiated by the Belgian State — Prime Minister's Service — Science Policy Office. The scientific responsibility is assumed by its authors.
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References
Borgefors, G.: Distance transformations in arbitrary dimensions. Computer Vision, Graphics and Image Processing 27(3) (1984) 321–345
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Embrechts, H., Roose, D.: Parallel algorithms for the distance transformation. Technical Report TW151 (1991) Katholieke Universiteit Leuven
Embrechts, H., Roose, D., Wambacq, P.: Component labelling on an mimd multiprocessor. Computer Vision, Graphics and Image Processing: Image Understanding, to appear
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© 1992 Springer-Verlag Berlin Heidelberg
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Embrechts, H., Roose, D. (1992). Parallel algorithms for the distance transformation. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_44
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DOI: https://doi.org/10.1007/3-540-55426-2_44
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