thresholding {magick} | R Documentation |
Image thresholding
Description
Thresholding an image can be used for simple and straightforward image segmentation.
The function image_threshold()
allows to do black and white thresholding whereas
image_lat()
performs local adaptive thresholding.
Usage
image_threshold(
image,
type = c("black", "white"),
threshold = "50%",
channel = NULL
)
image_level(
image,
black_point = 0,
white_point = 100,
mid_point = 1,
channel = NULL
)
image_lat(image, geometry = "10x10+5%")
Arguments
image |
magick image object returned by |
type |
type of thresholding, either one of lat, black or white (see details below) |
threshold |
pixel intensity threshold percentage for black or white thresholding |
channel |
a value of |
black_point |
value between 0 and 100, the darkest color in the image |
white_point |
value between 0 and 100, the lightest color in the image |
mid_point |
value between 0 and 10 used for gamma correction |
geometry |
pixel window plus offset for LAT algorithm |
Details
-
image_threshold(type = "black")
: Forces all pixels below the threshold into black while leaving all pixels at or above the threshold unchanged -
image_threshold(type = "white")
: Forces all pixels above the threshold into white while leaving all pixels at or below the threshold unchanged -
image_lat()
: Local Adaptive Thresholding. Looks in a box (width x height) around the pixel neighborhood if the pixel value is bigger than the average minus an offset.
Examples
test <- image_convert(logo, colorspace = "Gray")
image_threshold(test, type = "black", threshold = "50%")
image_threshold(test, type = "white", threshold = "50%")
# Turn image into BW
test |>
image_threshold(type = "white", threshold = "50%") |>
image_threshold(type = "black", threshold = "50%")
# adaptive thresholding
image_lat(test, geometry = '10x10+5%')