8.2. Differenz der Mittelwerte

8.2.1. Wirkungsweise

Abbildung 17.169. Anwendungsbeispiel für das Filter „Differenz der Mittelwerte“

Anwendungsbeispiel für das Filter „Differenz der Mittelwerte“

Originalbild

Anwendungsbeispiel für das Filter „Differenz der Mittelwerte“

Filter „Difference of Gaussians“ applied with radius 1 = 1.000 and radius 2 = 0.100.


This filter does edge detection using the so-called „Difference of Gaussians“ algorithm, which works by performing two different Gaussian blurs on the image, with a different blurring radius for each, and subtracting them to yield the result.

This algorithm is very widely used in artificial vision, and is pretty fast because there are very efficient methods for doing Gaussian blurs.

8.2.2. Activating the Filter

This filter is found in the main menu under Filters → Edge-Detect → Difference of Gaussians….

8.2.3. Eigenschaften

Abbildung 17.170. Eigenschaften für das Filter „Differenz der Mittelwerte“

Eigenschaften für das Filter „Differenz der Mittelwerte“

Presets, „Input Type“, Clipping, Blending Options, Vorschau, Merge filter, Split view
[Anmerkung] Anmerkung

These options are described in Abschnitt 2, „Gemeinsame Funktionsmerkmale“.

Radius 1, Radius 2

Radius 1 and Radius 2 are the blurring radii for the two Gaussian blurs. Increasing „Radius 1“ tends to give thicker-appearing edges, and decreasing the „Radius 2“ tends to increase the „threshold“ for recognizing something as an edge.

If you want to produce something that looks like a sketch, in most cases setting „Radius 2“ smaller than „Radius 1“ will give better results.

In situations where you have a light figure on the dark background, reversing them may actually improve the result.