Removing Contour around a certain color - opencv

Question

So i have a skin color range that I'm using to draw the contours of any skin color my camera sees, i.e, it'll draw contour on the hands or faces etc.
However, the range of color that I am using to draw the contours has a red range of 0-255, so it basically draws contour around everything that is red. The red pixel is however important for a good skin detection so I can't change that.
So i was wondering how I could tweek my contour code, so that it doesn't draw contour around the color red.
My code is as follow:
min_YCrCb = np.array([0,133,77],np.uint8) # Create a lower bound for the skin color
max_YCrCb = np.array([255,173,127],np.uint8) # Create an upper bound for skin color
skinRegion = cv2.inRange(converted,min_YCrCb,max_YCrCb) # Create a mask with boundaries
contours, hierarchy = cv2.findContours(skinRegion, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Find the contour on the skin detection
for i, c in enumerate(contours): # Draw the contour on the source frame
area = cv2.contourArea(c)
if area > 10000:
cv2.drawContours(img, contours, i, (255, 255, 0), 2)

Answer 1

In my experience with OpenCV, and what many other would recommend, would be converting your RGB color scheme into HSV.
HSV stands for Hue, Saturation, and Value and is just another way of expressing different colors in the white light spectrum. In RGB it can be very difficult to find bright or dull colors but this is not the case in the HSV color range.
In the Python documentation of OpenCV one can see an example of converting BGR to HSV, NOTE: The H in HSV has a range of 0-179 while the others are 0-255.
You can switch to HSV by using the function hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) and then having your code find the contours within that image stream instead of your original. To figure out what your HSV range should be set to, you can google a RGB to HSV converter such as this one - NOTE: OpenCV commonly uses BGR instead of RBG so be careful not to get them mixed up
This should help you find the exact range of colors you need to make sure your program is properly working.
min_YCrCb = np.array([0,0,0],np.uint8) # Create a lower bound HSV
max_YCrCb = np.array([179,255,255],np.uint8) # Create an upper bound HSV
hsv = cv2.cvtColor(converted, cv2.COLOR_BGR2HSV) # assuming converted is your original stream...
skinRegion = cv2.inRange(hsv,min_YCrCb,max_YCrCb) # Create a mask with boundaries
contours, hierarchy = cv2.findContours(skinRegion, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Find the contour on the skin detection
for i, c in enumerate(contours): # Draw the contour on the source frame
area = cv2.contourArea(c)
if area > 10000:
cv2.drawContours(img, contours, i, (255, 255, 0), 2)