What is the example reference threshold for each component of a LAB image?

I'm doing a project of face skin detection. I need to replace each pixel in a face image with a black pixel if the image intensity is less than some fixed constant T, or a white pixel if the image intensity is greater than that constant.

I know in opencv, cv2.threshold takes two arguments, First argument is the source image, which should be a grayscale image. Second argument is the threshold value which is used to classify the pixel values.

Can anybody tell me how to threshold color images by designating a separate threshold for each of the LAB components of the image and then combine them with an AND operation?

Example threshold ranges would be great!

here is an sample code i wrote:

import cv2

color_image = cv2.imread("lena.png")
lab_image = cv2.cvtColor(color_image, cv2.COLOR_BGR2LAB)
L,A,B=cv2.split(lab_image)  

th, th_image = cv2.threshold(L,100,255,cv2.THRESH_BINARY)

#cv2.imshow("original",color_image)
#cv2.imshow("l space",L)
cv2.imshow("th imaged",th_image)


# wait until escape is pressed
while True:
    keyboard = cv2.waitKey()
    if keyboard == 27:
        break

cv2.destroyAllWindows()

here is the official doc:

cv.Threshold(src, dst, threshold, maxValue, thresholdType) → None

Parameters:

• src – input array (single-channel, 8-bit or 32-bit floating point).
  • dst – output array of the same size and type as src.
  • thresh – threshold value.
  • maxval – maximum value to use with the THRESH_BINARY and THRESH_BINARY_INV thresholding types.
  • type – thresholding type (see the details below).

the code will generate you these three images:

Original:

L-Space of the LAB Convertion:

and finally a simple threshold example:

a rly good tutorial can be found here for tresholding: OpenCV