Crop subimage from image with Edge Detection

Question

So basically I have an image with whitespace and a text above. The output should be only the picture. Without the text and the whitespaces. The best example would probably be a meme:

I believe I would have to get the corner coordinates and then use something like pillow's Image.crop(corner_coordinates).

How could I implement this?

Edit: So I tried a little bit. I used the Canny Edge Detection Algorithm (opencv). Im now getting the desired edges bit also the edges from the text. Would be nice if someone could help me:)

Answer 1

You may find bounding rectangle of the largest contour that is not white.

I suggest using the following stages:

• Convert image from BGR to Gray.
• Convert from gray to to binary image.
  Use automatic threshold (use cv2.THRESH_OTSU flag) and invert polarity.
  The result is white color where original image is dark, and black where image is bright.
• Find contours using cv2.findContours() (as Mark Setchell commented).
  Finding the outer contour is simpler solution than detecting the edges.
• Find the bounding rectangle of the contour with the maximum area.
• Crop the bounding rectangle from the input image.
  I used NumPy array slicing instead of using pillow.

Here is the code:

import cv2

# Read input image
img = cv2.imread('img.jpg')

# Convert from BGR to Gray.
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Convert to binary image using automatic threshold and invert polarity
_, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

# Find contours on thresh
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)[-2]  # Use index [-2] to be compatible to OpenCV 3 and 4

# Get contour with maximum area
c = max(cnts, key=cv2.contourArea)

x, y, w, h = cv2.boundingRect(c)

# Crop the bounding rectangle (use .copy to get a copy instead of slice).
crop = img[y:y+h, x:x+w, :].copy()


# Draw red rectangle for testing
cv2.rectangle(img, (x, y), (x+w, y+h), (0, 0, 255), thickness = 2)

# Show result
cv2.imshow('img', img)
cv2.imshow('crop', crop)
cv2.waitKey(0)
cv2.destroyAllWindows()

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Result:

crop:

img:

thresh: