Obtaining binary mask of skin from bounding box

Question

I have trained an object detection model to detect fingertips of hand. I have extracted the fingertips from the bounding box coordinates. Here is what I got:

Now I want to get the binary mask from these images, which include only the region of fingertip. I have tried these approaches and did not get satisfactory results.

• Used canny edge detector approach.
• Used Grabcut approach.
• Normalized image, then extracted h channel from HSV to find the largest contour.

I want to extract the fingertip region from these bounding boxes, I am currently lost, will appreciate any leads in the right direction.

EDIT Images with red background:

Answer 1

You can opt for the LAB color space.

One extreme of the A-channel identifies red color. Hence applying Otsu threshold on this extreme can isolate it pretty well.

Code:

img = cv2.imread('finger_1.png')

# convert to LAB color space
lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)

# apply Otsu threshold on A-channel
th = cv2.threshold(lab[:,:,1], 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

Results:

As a further option, you can try normalizing the same A-channel and proceed further.

Also have a look at this post on how to segment green color.