How to detect black contour in image using open-cv

Question

I have an image showed below (this image is a result of pre-processing of original image I had):

What I am trying to do is to detect the contour for the Black region bounded by 2 white regions (please note that white regions are not always solid and there could be 2, 3,... disconnected white region on top - for most of pictures the white regions are continuous; however, there are some examples where top white region is not continuous - Please see update section of my question to see example of non-continuous region)

Do you have any suggestion as how I can detect the boundary of black region and separate the black region?

Answer 1

Here is how:

import cv2
import numpy as np

img = cv2.imread(r"D:\OpenCV Projects\Black Contour\image.jpg")

img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lower = np.array([0, 0, 75])
upper = np.array([179, 179, 115])
mask = cv2.inRange(img_hsv, lower, upper)

mask_blur = cv2.GaussianBlur(mask, (3, 3), 1)
_, thresh = cv2.threshold(mask_blur, 200, 255, cv2.THRESH_BINARY)

contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

cv2.drawContours(img, [max(contours, key=cv2.contourArea)], -1, (255, 0, 0), 3)
cv2.imshow("Image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

Here is all the processing the image went through during the execution of the above code:

BGR to HSV:

HSV to mask:

Mask to blurred mask:

Blurred mask to thresholded mask:

From here, simply detect the contour from the image above and draw it onto the image.