Estimates cornerness for pre-specified KeyPoints using the FAST algorithm

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

Input

• im 8-bit grayscale image where keypoints (corners) are to be detected.
• keypoints keypoints which should be tested to fit the FAST criteria. A 1-by-N structure array, with at least the "pt" field filled. In the output, keypoints not being detected as corners are removed.

Output

• keypoints Keypoints detected on the image. With their "response" field calculated.

Options

• Threshold Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel. 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].

Rational: Some applications only want to know if there are feature at specific locations. To fit these needs the cv.FAST approach is extended in cv.FASTForPointSet to recieve a vector of locations and calculates the FAST response on these positions. If it is below the threshold, it will be removed from the list.

References

[Rosten06]:

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