The k-distance transformation (k-DT) computes the k nearest patterns from each location on a discrete regular grid within a D dimensional volume, which Warfield [Patt. Rec. Letters, 17(1996) 713-721] proposed to implement using 2^D raster scans. We investigate the possible approaches for efficient implementations by extending the existing Euclidean 1-DT methods and propose two new k-DT algorithms. The first is based on ordered propagation while the second divides the problem into D 1-dimensional problems. We compare the computational complexity of the different approaches.
Aude Billard, Mikhail Koptev, Nadia Barbara Figueroa Fernandez
Giovanni De Micheli, Massimiliano Di Ventra
Negar Kiyavash, Sina Akbari, Seyed Jalal Etesami