Issue
This is a truck container image but from the top view. First, I need to find the rectangle and know each corner position. The goal is to know the dimension of the container.
Solution
Here's a simple approach:
Obtain binary image. Load image, convert to grayscale, Gaussian blur, then Otsu's threshold.
Find distorted bounding rectangle contour and corners. We find contours then filter using contour area to isolate the rectangular contour. Next we find the distorted bounding rectangle with
cv2.minAreaRect()
and the corners withcv2.boxPoints()
Detected bounding rectangle ->
Mask ->
Detected corners



Corner points
(188, 351)
(47, 348)
(194, 32)
(53, 29)
Code
import cv2
import numpy as np
# Load image, grayscale, blur, Otsu's threshold
image = cv2.imread('1.png')
mask = np.zeros(image.shape[:2], dtype=np.uint8)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5,5), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
# Find distorted bounding rect
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
area = cv2.contourArea(c)
if area > 5000:
# Find distorted bounding rect
rect = cv2.minAreaRect(c)
corners = cv2.boxPoints(rect)
corners = np.int0(corners)
cv2.fillPoly(mask, [corners], (255,255,255))
# Draw corner points
corners = corners.tolist()
print(corners)
for corner in corners:
x, y = corner
cv2.circle(image, (x, y), 5, (36,255,12), -1)
cv2.imshow('thresh', thresh)
cv2.imshow('image', image)
cv2.imshow('mask', mask)
cv2.waitKey()
Answered By - nathancy Answer Checked By - Dawn Plyler (PHPFixing Volunteer)
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