How do you lightness thresh hold with HSL on OpenCV?

Question

There is a project that im working on which required the color white detection, after some research i decided to use covert RGB image to HSL image and thresh hold the lightness to get the color white, im working with openCV so wonder if there is a way to do it. enter image description here

Autoerotism

in opencv is HLS and normally images are loaded as BGR in OpenCV. take a look to cvtColor. – Tribromoethanol

Yes i was able to covert the BGR to HLS but what i was stuck at how to filt out the pixel that have lightness attribute too low, so that the image will be left with the shade of color white – Autoerotism

use split to separate the channels (or using numpy slicing), then use threshold in the L one (second channel) and you get a mask with it, then apply the mask to your original image. If you post an example image I can try to give a complete answer – Tribromoethanol

Answer 1

You can do it with 4 easy steps:

Convert HLS

img = cv2.imread("HLS.png")
imgHLS = cv2.cvtColor(img, cv2.COLOR_BGR2HLS)

Get the L channel

Lchannel = imgHLS[:,:,1]

Create the mask

#change 250 to lower numbers to include more values as "white"
mask = cv2.inRange(Lchannel, 250, 255)

Apply Mask to original image

res = cv2.bitwise_and(img,img, mask= mask)

This also depends on what is white for you, and you may change the values :) I used inRange in the L channel but you can save one step and do

mask = cv2.inRange(imgHLS, np.array([0,250,0]), np.array([255,255,255]))

instead of the lines:

Lchannel = imgHLS[:,:,1]
mask = cv2.inRange(Lchannel, 250, 255)

It is shorter, but I did it the other way first to make it more explicit and to show what I was doing.

Image:

Result:

The result looks almost as the mask (almost binary), but depending on your lowerbound (I chose 250) you may get even some almost white colors.

Tribromoethanol