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conference paper
The Euclidean k-Distance Transformartion in Arbitrary Dimensions - a Separable Implementation
2005
International Conference on Image Processing - ICIP'05
The signed k-distance transformation (k-DT) computes the k nearest prototypes from each location on a discrete regular grid within a given D dimensional volume. We propose a new k-DT algorithm that divides the problem into D 1-dimensional problems and compare its accuracy and computational complexity to the existing raster-scanning and propagation approaches.
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Cuisenaire2005_1251.pdf
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openaccess
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90.92 KB
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Adobe PDF
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