Detects corners using the FAST algorithm

keypoints = cv.FAST(im)
keypoints = cv.FAST(im, 'OptionName', optionValue, ...)

Input

• im 8-bit grayscale image where keypoints (corners) are to be detected.

Output

• keypoints Keypoints detected on the image. A 1-by-N structure array. It has the following fields:
  • pt coordinates of the keypoint [x,y]
  • size diameter of the meaningful keypoint neighborhood
  • angle computed orientation of the keypoint (-1 if not applicable). Its possible values are in a range [0,360) degrees. It is measured relative to image coordinate system (y-axis is directed downward), ie in clockwise.
  • response the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling.
  • octave octave (pyramid layer) from which the keypoint has been extracted.
  • class_id object id that can be used to clustered keypoints by an object they belong to.

Options

• Threshold Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel. See the algorithm description [Rosten06]. default 10.
• NonmaxSuppression If it is true, non-maximum supression is applied to detected corners (keypoints). default true.
• Type one of the three neighborhoods as defined in the paper:
  • TYPE_9_16 (default)
  • TYPE_7_12
  • TYPE_5_8

Detects corners using the FAST algorithm by [Rosten06].

References

[Rosten06]:

E. Rosten (Machine Learning for High-speed Corner Detection, 2006).