Finding the convex hull of a contour area

Once we have identified the largest contour in our mask, it is straightforward to compute the convex hull of the contour area. The convex hull is basically the envelope of the contour area. If you think of all the pixels that belong to the contour area as a set of nails poking out of a board, then a tight rubber band encircles all the nails forming the convex hull shape. We can get the convex hull directly from our largest contour (max_contour), like this:

hull = cv2.convexHull(max_contour, returnPoints=False) 

As we now want to look at convexity deficits in this hull, we are instructed by the OpenCV documentation to set the returnPoints optional flag to False.

The convex hull drawn in yellow around a segmented hand region looks like this:

As mentioned previously, we will determine a hand gesture based on convexity defects. Let's move on and learn how to find the convexity defects of a convex hull in the next section, which will bring us one step closer to recognizing hand gestures.