Corner detection

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

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