The Distance Transform and its Computation

06/07/2021
by   Tilo Strutz, et al.
0

Distance transformation is an image processing technique used for many different applications. Related to a binary image, the general idea is to determine the distance of all background points to the nearest object point (or vice versa). In this tutorial, different approaches are explained in detail and compared using examples. Corresponding source code is provided to facilitate own investigations. A particular objective of this tutorial is to clarify the difference between arbitrary distance transforms and exact Euclidean distance transformations.

READ FULL TEXT

page 2

page 3

page 8

page 11

research
12/17/2018

Computing the Hausdorff Distance of Two Sets from Their Signed Distance Functions

The Hausdorff distance is a measure of (dis-)similarity between two sets...
research
10/18/2018

Stochastic Distance Transform

The distance transform (DT) and its many variations are ubiquitous tools...
research
03/21/2016

Nearest Points on Toric Varieties

We determine the Euclidean distance degree of a projective toric variety...
research
05/05/2014

Comparing apples to apples in the evaluation of binary coding methods

We discuss methodological issues related to the evaluation of unsupervis...
research
04/24/2013

k-Modulus Method for Image Transformation

In this paper, we propose a new algorithm to make a novel spatial image ...
research
12/11/2019

Bottleneck detection by slope difference distribution: a robust approach for separating overlapped cells

To separate the overlapped cells, a bottleneck detection approach is pro...

Please sign up or login with your details

Forgot password? Click here to reset