Rvision (version 0.4.2)

adaptiveThreshold: Adaptive Thresholding

Description

adaptiveThreshold transforms a grayscale image to a binary image using an adaptive threshold.

Usage

adaptiveThreshold(
  image,
  max_value = 255,
  method = "mean",
  threshold_type = "inverse",
  block_size = 31,
  C = 25,
  in_place = FALSE
)

Arguments

image

An an 8-bit (8U) single-channel Image object.

max_value

Non-zero numerical value assigned to the pixels above the adaptive threshold (default: 255).

method

The name of the adaptive thresholding algorithm to use. It can be either 'mean' - mean of the block_size * block_size neighborhood - or 'gaussian' - Gaussian weighted sum of the block_size * block_size neighborhood (default: 'mean').

threshold_type

The name of the threshold type to use. It can be either 'binary' or 'inverse' (default: 'inverse').

block_size

Size of a pixel neighborhood that is used to calculate a threshold value for the pixel (default: 31).

C

Constant subtracted from the mean or weighted mean. Normally, it is positive but may be zero or negative as well (default: 25).

in_place

A logical indicating whether the change should be applied to the image itself (TRUE, faster but destructive) or to a copy of it (FALSE, the default, slower but non destructive).

Value

An Image object if in_place=FALSE. Otherwise, it returns nothing and modifies image in place.

See Also

Image

Examples

# NOT RUN {
balloon <- image(system.file("sample_img/balloon1.png", package = "Rvision"))
balloon_gray <- changeColorSpace(balloon, "GRAY")
balloon_th <- adaptiveThreshold(balloon_gray)
plot(balloon_th)

# }