edge detection (Frei_chen, LoG, Prewitt, Roberts_cross, Scharr, Sobel)
edge detection (Frei_chen, LoG, Prewitt, Roberts_cross, Scharr, Sobel)
edge_detection( image, method = NULL, conv_mode = "same", approx = F, gaussian_dims = 5, sigma = 1, range_gauss = 2, laplacian_type = 1 )
image |
matrix or 3-dimensional array |
method |
the method should be one of 'Frei_chen', 'LoG' (Laplacian of Gaussian), 'Prewitt', 'Roberts_cross', 'Scharr', 'Sobel' |
conv_mode |
the convolution mode should be one of 'same', 'full' |
approx |
if TRUE, approximate calculation of gradient (applies to all filters except for 'LoG') |
gaussian_dims |
integer specifying the horizontal and vertical dimensions of the gaussian filter |
sigma |
float parameter sigma for the gaussian filter |
range_gauss |
float number specifying the range of values for the gaussian filter |
laplacian_type |
integer value specifying the type for the laplacian kernel (one of 1, 2, 3, 4) |
This function takes either a matrix or a 3-dimensional array and it performs edge detection using one of the following filters : 'Frei_chen', 'LoG' (Laplacian of Gaussian), 'Prewitt', 'Roberts_cross', 'Scharr', 'Sobel'
depending on the input, either a matrix or an array
Lampros Mouselimis
path = system.file("tmp_images", "1.png", package = "OpenImageR")
image = readImage(path)
res = edge_detection(image, method = 'Frei_chen', conv_mode = 'same')Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.