Corner detection

../../../../_images/image_corners.svg

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.CornerDetection[source]

Detects corners in the incoming image

Algorithms:
  • FAST

    Corner detection using the FAST (Feature from Accelerated Segment Test) method.

    n:

    Number of points out of 16 that should be all brighter ordarker than test point. (default 12)

    threshold:

    Threshold used in determining wheter the pixels are darker orbrighter (default 0.15).

    Decrease threshold when more corners are desired

  • KR

    Compute Kitchen-Rosenfeld corner measure response image

    k:

    Value outside image borders when method constant is used.

    border mode:

    Method for handling values outside the borders

  • ST

    Compute Shi-Tomasi (Kanade-Tomasi) corner measure responseimage. Uses information from auto-correlation matrix

    sigma:

    Standard deviation used for the Gaussian kernel, which is used as weighting function for the auto-correlation matrix.

  • harris

    Compute corner harris response image.

    harris method:

    Method to compute response image from auto-correlationmatrix

    k:

    Sensitivity factor to separate corners from edges, typically in range [0, 0.2]. Small values of k result in detection of sharp corners.

    eps:

    Normalisation factor (Nobles corner measure)

    sigma:

    Standard deviation used for the Gaussian kernel, which is used as weighting function for the auto-correlation matrix.

  • moravec

    Compute Moravec corner measure response image.

    This is one of the simplest corner detectors and is comparatively fast but has several limitations (e.g. not rotation invariant).

    window size:

    Size of window used during calculations

Inputs:

source : image

source image to filter

Outputs:

result : image

result after filtering