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OpenCV keypoints

Source: R/keypoints.R
ocv_keypoints.Rd

Find key points in images

Usage

ocv_keypoints(
  image,
  method = c("FAST", "Harris"),
  control = ocv_keypoints_options(method, ...),
  ...
)

Arguments

image

an ocv grayscale image object

method

the type of keypoint detection algorithm

control

a list of arguments passed on to the algorithm

...

further arguments passed on to ocv_keypoints_options

FAST algorithm arguments

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

  • nonmaxSuppression if true, non-maximum suppression is applied to detected corners (keypoints).

  • type one of the three neighborhoods as defined in the paper: TYPE_9_16, TYPE_7_12, TYPE_5_8

Harris algorithm arguments

  • numOctaves the number of octaves in the scale-space pyramid

  • corn_thresh the threshold for the Harris cornerness measure

  • DOG_thresh the threshold for the Difference-of-Gaussians scale selection

  • maxCorners the maximum number of corners to consider

  • num_layers the number of intermediate scales per octave

Examples

mona <- ocv_read('https://jeroen.github.io/images/monalisa.jpg')
mona <- ocv_resize(mona, width = 320, height = 477)

# FAST-9
pts <- ocv_keypoints(mona, method = "FAST", type = "TYPE_9_16", threshold = 40)
#> Keypoint detection disabled as module xfeatures2d from opencv_contrib is not present.
# Harris
pts <- ocv_keypoints(mona, method = "Harris", maxCorners = 50)
#> Keypoint detection disabled as module xfeatures2d from opencv_contrib is not present.

# Convex Hull of points
pts <- ocv_chull(pts)

# \dontshow{
ocv_destroy(mona)
# }