pimage 1.0.6

Library for detecting image copy-move attack

This is a python package for detecting copy-move attack on a digital image.

More documentation is detailed on the Github page.

Example usage

API for the detection process

from pimage import copy_move

fraud_list, ground_truth_image, result_image = copy_move.detect("dataset_example_blur.png", block_size=32)

• fraud_list will be the list of (x_coordinate, y_coordinate) and the number of the blocks. If the list is not empty, we can assume that the image is being tampered. For example:

  ((-57, -123), 2178)
  ((-11, 140), 2178)
  ((-280, 114), 2178)
  ((-34, -305), 2178)
  ((-37, 148), 2178)
  

  means there are 5 possible matched/identical region with 2178 overlapping blocks on each of it
• ground_truth_image contains the black and white ground truth of the detection result
• result_image is the given image where the possible fraud region will be bordered (if any)

ground_truth_image and result_image will be formatted as numpy.ndarray. It can further be processed. For example, it can be exported as image like so:

import imageio

imageio.imwrite("result_image.png", result_image)
imageio.imwrite("ground_truth_image.png", ground_truth_image)

Quick command to detect an image

To quickly run the detection command for your image, the copy_move.detect_and_export() is also provided. The command is identical with .detect() but it also save the result to desired output path.

from pimage import copy_move

copy_move.detect_and_export('dataset_example_blur.png', 'output', block_size=32)