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Corner detector
f = icorner(im, options) is a vector of PointFeature objects describing corner features detected in the image im. This is a non-scale space detector and by default the Harris method is used but Shi-Tomasi and Noble are also supported.
If im is an image sequence a cell array of PointFeature vectors for the correspnding frames of im.
The PointFeature object has many properties including:
u | horizontal coordinate |
v | vertical coordinate |
strength | corner strength |
descriptor | corner descriptor (vector) |
See PointFeature for full details
'detector', D | choose the detector where D is one of 'harris' (default), 'noble' or 'klt' |
'sigma', S | kernel width for smoothing (default 2) |
'deriv', D | kernel for gradient (default kdgauss(2)) |
'cmin', CM | minimum corner strength |
'cminthresh', CT | minimum corner strength as a fraction of maximum corner strength |
'edgegap', E | don't return features closer than E pixels to the edge of image (default 2) |
'suppress', R | don't return a feature closer than R pixels to an earlier feature (default 0) |
'nfeat', N | return the N strongest corners (default Inf) |
'k', K | set the value of k for the Harris detector |
'patch', P | use a PxP patch of surrounding pixel values as the feature vector. The vector has zero mean and unit norm. |
'color' | specify that IM is a color image not a sequence |
Compute the 100 strongest Harris features for the image
c = icorner(im, 'nfeat', 100);
and overlay them on the image
idisp(im); c.plot();
© 1990-2012 Peter Corke.