Watermarking-based image authentication with recovery capability using halftoning technique

In this paper two watermarking algorithms for image content authentication with localization and recovery capability of the tampered regions are proposed. In both algorithms, a halftone version of the original gray-scale image is used as an approximated version of the host image (image digest) which is then embedded as a watermark sequence into given transform domains of the host image. In the first algorithm, the Integer Wavelet Transform (IWT) is used for watermark embedding which is denominated WIA-IWT (Watermarking-based Image Authentication using IWT), while in the second one, the Discrete Cosine Transform (DCT) domain is used for this purpose, we call this algorithm WIA-DCT (Watermarking-based Image Authentication using DCT). In the authentication stage the tampered regions are detected using the Structural Similarity index (SSIM) criterion, which are then recovered using the extracted halftone image. In the recovery stage, a Multilayer Perceptron (MLP) neural network is used to carry out an inverse halftoning process to improve the recovered image quality. The experimental results demonstrate the robustness of both algorithms against content preserved modifications, such as JPEG compression, as well as an effective authentication and recovery capability. Also the proposed algorithms are compared with some previously proposed content authentication algorithms with recovery capability to show the better performance of the proposed algorithms.