ocv_keypoints: OpenCV keypoints

In opencv: Bindings to 'OpenCV' Computer Vision Library

OpenCV keypoints

Description

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)
# Harris
pts <- ocv_keypoints(mona, method = "Harris", maxCorners = 50)

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

opencv documentation built on Oct. 4, 2024, 9:06 a.m.