Detecting and Localizing Copy-Move and Image-Splicing Forgery. (arXiv:2202.04069v1 [cs.CV])

In the world of fake news and deepfakes, there have been an alarmingly large
number of cases of images being tampered with and published in newspapers, used
in court, and posted on social media for defamation purposes. Detecting these
tampered images is an important task and one we try to tackle. In this paper,
we focus on the methods to detect if an image has been tampered with using both
Deep Learning and Image transformation methods and comparing the performances
and robustness of each method. We then attempt to identify the tampered area of
the image and predict the corresponding mask. Based on the results, suggestions
and approaches are provided to achieve a more robust framework to detect and
identify the forgeries.



Related post