Edge detection

Detects edges in the incoming image

Algorithms:

• canny

  Canny edge detection.

  sigma:

  Standard deviation of gaussian kernel (default 1.0)

• laplace

  Find edges using the Laplace operator.

  kernel size:

  Kernel size of the discrete Laplacian operator

• prewitt

  Find edges using the Prewitt transform as one of, or combination of horizontal and vertical prewitt convolutions

  horizontal/vertical:

  Select orientation for transform, if both then mean square of both will be used

• roberts

  Find edges using Robert’s cross operator.

  positive/negative diagonal:

  Select orientation for transform

• scharr

  Find edges using the Scharr transform as one of, or combination of horizontal and vertical prewitt convolutions.

  The Scharr operator has a better rotation invariance than other edge filters such as the Sobel or the Prewitt operators

  horizontal/vertical:

  Select orientation for transform, if both then mean square of both will be used

• sobel

  Find edges using the Sobel transform as one of, or combination of horizontal and vertical prewitt convolutions.

  horizontal/vertical:

  Select orientation for transform, if both then mean square of both will be used

Inputs:

source : image

source image to filter

Outputs:

result : image

result after filtering

Input ports:

source:

image

source image to filter

Output ports:

result:

image

result after filtering

Configuration:

algorithm

(no description)

horizontal/vertical

(no description)

kernel size

(no description)

positive/negative diagonal

(no description)

sigma

(no description)

Some of the docstrings for this module have been extracted from the scikit-image library and are covered by their respective licenses.

class node_detection_filters.EdgeDetection