Add to ORKGIn this paper, digital distance functions using sequences of weights are studied and used to approximate the Euclidian distance. Sequences of weights that guarantee a low maximum absolute error for path lengths of up to 10000 are calculated. A necessary condition and a sufficient condition for metricity of this kind of distance function are established
We discuss a number of distance functions encountered in the theory of computation, includin
[sing a discrete distance transform one can quicicly build a map of the distance from a goal to ever...
AbstractPath-based distance functions are defined on n-dimensional generalizations of the face-cente...
AbstractIn image processing, the distance transform (DT), in which each object grid point is assigne...
International audienceIn this paper, a family of weighted neighborhood sequence distance functions d...
We compare the most frequently used algorithms for computing distance transforms in terms of speed, ...
AbstractA subclass of general octagonal distances defined by neighbourhood sequences [2] have been c...
International audienceIn image processing, the distancetransform (DT), in which each object grid poi...
International audienceIn recent years, the theory behind distance functions defined by neighbourhood...
In image processing, the distance transform (DT), in which each object grid point is assigned the di...
In analysis, a distance function (also called a metric) on a set of points S is a function d:SxS->R ...
The discrete Fréchet distance is a measure of similarity between point sequences which permits to a...
AbstractIn this paper, we examine five different three-dimensional grids suited for image processing...
AbstractA path-based distance is defined as the minimal cost-path between two points. One such dista...
Recently, a distance function was defined on the face-centered cubic and body-centered cubic grids b...
We discuss a number of distance functions encountered in the theory of computation, includin
[sing a discrete distance transform one can quicicly build a map of the distance from a goal to ever...
AbstractPath-based distance functions are defined on n-dimensional generalizations of the face-cente...
AbstractIn image processing, the distance transform (DT), in which each object grid point is assigne...
International audienceIn this paper, a family of weighted neighborhood sequence distance functions d...
We compare the most frequently used algorithms for computing distance transforms in terms of speed, ...
AbstractA subclass of general octagonal distances defined by neighbourhood sequences [2] have been c...
International audienceIn image processing, the distancetransform (DT), in which each object grid poi...
International audienceIn recent years, the theory behind distance functions defined by neighbourhood...
In image processing, the distance transform (DT), in which each object grid point is assigned the di...
In analysis, a distance function (also called a metric) on a set of points S is a function d:SxS->R ...
The discrete Fréchet distance is a measure of similarity between point sequences which permits to a...
AbstractIn this paper, we examine five different three-dimensional grids suited for image processing...
AbstractA path-based distance is defined as the minimal cost-path between two points. One such dista...
Recently, a distance function was defined on the face-centered cubic and body-centered cubic grids b...
We discuss a number of distance functions encountered in the theory of computation, includin
[sing a discrete distance transform one can quicicly build a map of the distance from a goal to ever...
AbstractPath-based distance functions are defined on n-dimensional generalizations of the face-cente...