Approximately locate an image within another

Question

I have this image of the world : And this image of europe : What technique could I use to approximately locate the image of europe within the world map?

Answer 1

Template matching is a technique for finding similar images within larger images, but it requires the template to be of the same size as in the sub-image. In this example OpenCV was used, but it can also be done using scikit-image.

import cv2
from imageio import imread

img = imread("https://i.sstatic.net/OIsWn.png", pilmode="L") 
template = imread("https://i.sstatic.net/fkNeW.png", pilmode="L")

# threshold images for equal colours
img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)[1]
template = cv2.threshold(template, 127, 255, cv2.THRESH_BINARY)[1]

aspect_ratio = template.shape[1] / template.shape[0]

# estimate the width and compute the height based on the aspect ratio
w = 380
h = int(w / aspect_ratio)

# resize the template to match the sub-image as best as possible
template = cv2.resize(template, (w, h))

result = cv2.matchTemplate(img, template, cv2.TM_CCOEFF)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)

top_left = max_loc
bottom_right = (top_left[0] + w, top_left[1] + h)

cv2.rectangle(img, top_left, bottom_right, 127, 3)

cv2.imwrite("europe_bounding_box.png", img)

Result:

Although this example uses a predetermined estimated width, it is also possible to test a range of possible widths and determine which value results in the best match.