Blind Image Watermarking

Abstract

This paper presents a robust image watermarking scheme based on a sample projection approach. While we consider the human visual system in our watermarking algorithm, we use the low frequency components of image blocks for data hiding to obtain high robustness against attacks. We use four samples of the approximation coefficients of the image blocks to construct a line segment in the 2-D space. The slope of this line segment, which is invariant to the gain factor, is employed for watermarking purpose. We embed the watermarking code by projecting the line segment on some specific lines according to message bits. To design a maximum likelihood decoder, we compute the distribution of the slope of the embedding line segment for Gaussian samples. The performance of the proposed technique is analytically investigated and verified via several simulations. Experimental results confirm the validity of our model and its high robustness against common attacks in comparison with similar watermarking techniques that are invariant to the gain attack.

Existing System

Adopting auxiliary pilots through the watermarked signal known at both the encoder and decoder; Using spherical codewords with correlator decoders, or using angle QIM (AQIM); Introducing a domain in which the embedding process is invariant to the gain attack.

Proposed System

Digital watermarking is a technique for inserting information (the watermark) into an image, which can be later extracted or detected for variety of purposes including identification and authentication purposes. In this paper, we propose a novel gain invariant watermarking scheme based on a sample projection scheme. Embedding the watermark bits into the approximation coefficients of the image blocks makes the algorithm highly robust against noise and compression attacks. Any possible selection of four approximation coefficients, that may be selected using a secret key, constructs a line segment whose slope is considered for data hiding. We embed the watermark bits by projecting the line segment on some specific coding lines while preserving its center of mass. In this way, the slope of the line segment carries the watermark information while the distortion imposed to its constructive samples is minimal. Since our embedding process is linear, it can be denoted by multiplication of specific embedding matrices. To implement the maximum likelihood (ML) detector for data extraction.

Architecture