RGB to HSV and thresholding
This example illustrates how RGB to HSV (Hue, Saturation, Value) conversion can be used to facilitate segmentation processes. A simple segmentation of the image can then be effectively performed by a mere thresholding of the HSV channels.
using Images, TestImages, LinearAlgebra, Interact, ImageView rbg_img = testimage("lighthouse") hsv_img = HSV.(rbg_img) channels = float(channelview(hsv_img)) hue_img = channels[1,:,:] value_img = channels[3,:,:] saturation_img = channels[2,:,:] binary_img = zeros(size(hue_img)) @manipulate for hue in 0:255, saturation in 0:255, value in 0:255 fill!(binary_img, 0.0) for ind in eachindex(hue_img) if hue_img[ind] <= hue && saturation_img[ind] <= saturation/255 && value_img[ind] <= value/255 binary_img[ind] = 1 end end colorview(Gray, binary_img) end
Here's the result in IJulia:
You can click on the slider bars to change the threshold of hue, saturation and value. The obtained binary image can be used as a mask on the original RGB image.