Abstract
In image processing, it is often of great importance to have small rotational dependency for distance functions. We present an optimization for distances based on neighbourhood sequences for the face-centered cubic (fee) and body-centered cubic (bcc) grids. In the optimization, several error functions are used measuring different geometrical properties of the balls obtained when using these distances. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Nagy, B., & Strand, R. (2006). Approximating Euclidean distance using distances based on neighbourhood sequences in non-standard three-dimensional grids. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4040 LNCS, pp. 89–100). Springer Verlag. https://doi.org/10.1007/11774938_8
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
