Image authentication algorithm with recovery capabilities based on neural networks in the DCT domain

• Published in: IET image processing Vol. 8; no. 11; pp. 619 - 626
• Main Authors: El'arbi, Maher, Ben Amar, Chokri
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.11.2014
• Subjects: Algorithms; Alterations; Authentication; Blocking; DCT domain; DCT transform; Deterioration; discrete cosine transforms; frequency coefficients; image authentication algorithm; image coding; Image compression; image tampering; image watermarking; JPEG compression; neural nets; Neural networks; recovery capabilities; recovery data
• ISSN: 1751-9659; 1751-9667; 1751-9667
• DOI: 10.1049/iet-ipr.2013.0646

In this study, the authors propose an image authentication algorithm in the DCT domain based on neural networks. The watermark is constructed from the image to be watermarked. It consists of the average value of each 8 × 8 block of the image. Each average value of a block is inserted in another supporting block sufficiently distant from the protected block to prevent simultaneous deterioration of the image and the recovery data during local image tampering. Embedding is performed in the middle frequency coefficients of the DCT transform. In addition, a neural network is trained and used later to recover tampered regions of the image. Experimental results shows that the proposed method is robust to JPEG compression and can also not only localise alterations but also recover them.