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Theory, idea for finding copied shapes on an image – Photoshop

The description of my problem is simple, I fear that the problem isn’t that simple. I would like to find the copied, duplicated part on an image. Which part of the image is copied and pasted back to the same image to another position(for example by using Photoshop)?

enter image description here

Please check the attached image. The red rectangle containing the value 20 is moved from the price field to the validity field. Please note that the rectangle size and position isn’t fixed and unknown, it could vary, just the image is given, no other information.

Could you help me naming a theoretical method, idea, paper, people who are working on the problem above?

I posted my method to here(stackoverflow) instead of Computer Vision to reach as many people I can, because maybe the problem can be transformed. I could think a solution, like looking for the 2 largest rectangle which contain the same values inside a huge matrix(image).

Thanks for your help and time.

Note: I don’t want to use the metadata to detect the forgery.

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Answers


  1. 0

    If you have access to the digital version of the forgery, and the forger (or the author of the forger-creation software) is a complete idiot, it can be as simple as looking at the image metadata for signs of ‘shopping.

    If digital files has been “washed” to remove said signs, or the forgery has been printed and then scanned back to you, it is a MUCH harder problem, again unless the forgers are complete idiots.

    In the latter case you can only hope for making the forger’s work harder, but there is no way to make it impossible – after all, banknotes can be forged, and they are much better protected than train tickets.

    I’d start reading from here: http://www.cs.dartmouth.edu/farid/downloads/publications/spm09.pdf

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  2. 0

    SHIFT features can be used to identify “similar regions” that might have been copied from a different part of the image. A starting point can be to use OpenCV’s SHIFT demo (included in the library) and use parts of the image as input, to see where a rough match is available. Detailed matching can follow to see if the region actually is a copy.

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