The Euclidean k-Distance Transformartion in Arbitrary Dimensions - a Separable Implementation

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.


Published in:
International Conference on Image Processing - ICIP'05, 2, 658-661
Year:
2005
Publisher:
EUSIPCO
Keywords:
Laboratories:




 Record created 2006-06-14, last modified 2019-12-05

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)