Corner detection¶
Some of the docstrings for this module have been extracted from the scikit-image library and are covered by their respective licenses.
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class
node_detection_filters.
CornerDetection
[source]¶ Detects corners in the incoming image
Algorithms: -
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
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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
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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.
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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.
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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
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