I have the following image which is a receipt image and a lot of white space around the receipt in focus. I would like to crop the white space. I can't manually crop it so I'm looking for a way that I could do it.

Cropped one:

Tried this code from the following post: How to remove whitespace from an image in OpenCV?

gray = load_image(IMG_FILE) # image file
gray = 255*(gray < 128).astype(np.uint8)
coords = cv2.findNonZero(gray) # Find all non-zero points (text)
x, y, w, h = cv2.boundingRect(coords) # Find minimum spanning bounding box
rect = load_image(IMG_FILE)[y:y+h, x:x+w] # Crop the image - note we do this on the original image

it's cropping a tiny part of the white space.

Here's a simple approach:

1. Obtain binary image. Load the image, convert to grayscale, apply a large Gaussian blur, and then Otsu's threshold

2. Perform morphological operations. We first morph open with a small kernel to remove noise then morph close with a large kernel to combine the contours

3. Find enclosing bounding box and crop ROI. We find the coordinates of all non-zero points, find the bounding rectangle, and crop the ROI.

Here's the detected ROI to crop highlighted in green

Cropped ROI

import cv2# Load image, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread('1.jpg')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (25,25), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]# Perform morph operations, first open to remove noise, then close to combine
noise_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, noise_kernel, iterations=2)
close_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (7,7))
close = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, close_kernel, iterations=3)# Find enclosing boundingbox and crop ROI
coords = cv2.findNonZero(close)
x,y,w,h = cv2.boundingRect(coords)
cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 2)
crop = original[y:y+h, x:x+w]cv2.imshow('thresh', thresh)
cv2.imshow('close', close)
cv2.imshow('image', image)
cv2.imshow('crop', crop)
cv2.waitKey()