Corner detection
 
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 desiredKR 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 bordersST 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-correlationmatrixk: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 | 
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| Inputs: | source : image 
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| Outputs: | result : image 
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- Input ports:
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| source: | image source image to filter | 
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- Output ports:
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| result: | image result after filtering | 
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- Configuration:
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- algorithm
- (no description)
- border mode
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- eps
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- harris method
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- k
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- n
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- sigma
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- threshold
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- window size
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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]