Triangle detection using OpenCV

Question

I have the following sample image:

I want to fill these triangles in the corners with white color. How could I detect them using OpenCV? Of course, in this particular sample, I can just lean on the gradient or brightness. Nevertheless, in the future images won't be such perfectly shaped, so I am thinking of some shape detection.

I heard that shaped can usually be detected with, for example, Hough transform. But I do not know what I should start with.

Contour detection in OpenCV does not help since it finds too many candidates. I tried to use approxPolyDP with size = 3, but there was also no result (there were no such objects found).

These triangles will always be triangles, but they do not need to touch bars every time. They always will be at the edges of the image. They share approximately the same area among them.

I would like to be able to detect triangles and collect points corresponding to these triangles in some container.

Answer 1

I am able to detect the triangle with below code. I am finding all the contours in the image and then using approxPolyDP, I am able to find the triangle.

import cv2
import numpy as np
image_obj = cv2.imread('image.jpg')

gray = cv2.cvtColor(image_obj, cv2.COLOR_BGR2GRAY)

kernel = np.ones((4, 4), np.uint8)
dilation = cv2.dilate(gray, kernel, iterations=1)

blur = cv2.GaussianBlur(dilation, (5, 5), 0)


thresh = cv2.adaptiveThreshold(blur, 255, 1, 1, 11, 2)

# Now finding Contours         ###################
_, contours, _ = cv2.findContours(
    thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
coordinates = []
for cnt in contours:
        # [point_x, point_y, width, height] = cv2.boundingRect(cnt)
    approx = cv2.approxPolyDP(
        cnt, 0.07 * cv2.arcLength(cnt, True), True)
    if len(approx) == 3:
        coordinates.append([cnt])
        cv2.drawContours(image_obj, [cnt], 0, (0, 0, 255), 3)

cv2.imwrite("result.png", image_obj)

Output image

You can get contours in coordinates list.