Detect edges (amplitude and direction) using the Frei-Chen operator.
prewitt_amp calculates an approximation of the first derivative of the image data and is used as an edge detector. The filter is based on the following filter masks:
A =
1 sqrt(2) 1
0 0 0
-1 -sqrt(2) -1
B =
1 0 -1
sqrt(2) 0 -sqrt(2)
1 0 -1
The result image contains the maximum response of the masks A and
B. The edge directions are returned in ImageEdgeDir,
and are stored in 2-degree steps, i.e., an edge direction of
x degrees with respect to the horizontal axis is stored as
x / 2 in the edge direction image. Furthermore, the
direction of the change of intensity is taken into account. Let
[Ex,Ey] denote the image gradient. Then the
following edge directions are returned as r/2:
intensity increase Ex / Ey edge direction r from bottom to top 0 / + 0 from lower right to upper left + / - ]0,90[ from right to left + / 0 90 from upper right to lower left + / + ]90,180[ from top to bottom 0 / + 180 from upper left to lower right - / + ]180,270[ from left to right + / 0 270 from lower left to upper right - / - ]270,360[.Points with edge amplitude 0 are assigned the edge direction 255 (undefined direction).
|
Image (input_object) |
image(-array) -> object : byte |
| Input image. | |
|
ImageEdgeAmp (output_object) |
image(-array) -> object : byte |
| Edge amplitude (gradient magnitude) image. | |
|
ImageEdgeDir (output_object) |
image(-array) -> object : direction |
| Edge direction image. | |
read_image(:Image:'fabrik':) > frei_dir(Image:Frei_dirA,Frei_dirD::) > threshold__(Frei_dirA:Res:128,255:).
frei_dir always returns TRUE. If the input is empty the behaviour can be set via set_system(::'no_object_result',<Result>:). If necessary, an exception is raised.
gauss__, sigma__, median, smooth__
hysteresis_threshold__, threshold__, grey_skeleton__, nonmax_suppression_dir, close_edges1, close_edges2
edges__, sobel_dir, robinson_dir, prewitt_dir, kirsch_dir