2D Cross-Correlation between Images

Computer Vision
Signal Processing

Difficulty: 2 | Problem written by mesakarghm
Write a function xcorr(x,y) which computes the cross-correlation to find the location of a template (y) in a noisy image (x).
The output of the function should be a tuple(a,b) representing the location of the template in the noisy image.

Feel free to use any library/function you see fit to achieve this task.

Sample Input:
<class 'list'>
x: [[1, 2, 3], [4, 5, 6]]
<class 'list'>
y: [[1, 2, 3], [4, 5, 6]]

Expected Output:
<class 'tuple'>
(2, 1)

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Jump to comment-139
abhishek_kumar • 3¬†months, 1¬†week ago


from scipy import signal
import numpy as np
def xcorr(x,y):
    corr = signal.correlate2d(x,y,boundary='symm', mode='same')
    b,a = np.unravel_index(np.argmax(corr), corr.shape)
    return (a,b)

Basically, this function is being used to locate a portion of the image on a real image.

It works on the principle of Fourier transformation of an image where the spatial format of the image donor provides us with much information.

Fourier format is easy to process.

For achieving more compact image representation






3. Convolution and Correlation

4. Fourier transform of images



Input Test Case

Please enter only one test case at a time
numpy has been already imported as np (import numpy as np)