Copy-move document image forgery detection and localization based on JPEG clues

A. V. Chuiko; K. B. Bulatov; D. V. Tropin

doi:10.1117/12.3023365

3 April 2024 Copy-move document image forgery detection and localization based on JPEG clues

A. V. Chuiko, K. B. Bulatov, D. V. Tropin

Proceedings Volume 13072, Sixteenth International Conference on Machine Vision (ICMV 2023); 130720K (2024) https://doi.org/10.1117/12.3023365
Event: Sixteenth International Conference on Machine Vision (ICMV 2023), 2023, Yerevan, Armenia

Abstract

The amount of image forgery strongly increases recently. There are different ways to fake an image, one of the common ones is a copy-move manipulation. There are numerous methods for detecting copy-move manipulations on natural images. However, they are difficult to adapt for document images due to their features. This work proposes an algorithm for detecting and localizing copy-move manipulations on digital images of documents. The main idea is to use JPEG artifacts in order to find the target region area and then localize the source and target regions precisely. For the efficient application of the proposed method, firstly, the original image must have been subjected to JPEG compression, and secondly, after the manipulation the image must have been saved in a lossless format. The experiments were carried out on an open set of document images CMID; in the detection task, the recall was 0.992, the specificity was 1.0; in the localization task, the recall was 0.923, the false discovery rate was 0.021, which means that the proposed algorithm successfully detects more than 99% of copy-move manipulations, similar to manipulations in the CMID and does not give false positives.

Citation Download Citation

A. V. Chuiko, K. B. Bulatov, and D. V. Tropin "Copy-move document image forgery detection and localization based on JPEG clues", Proc. SPIE 13072, Sixteenth International Conference on Machine Vision (ICMV 2023), 130720K (3 April 2024); https://doi.org/10.1117/12.3023365

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available