Contourlet Domain Feature Extraction for Image Content Authentication

The achievement of multimedia content authentication by means of digital watermarking, while never easy, is further complicated by the continuing investigation of different ways of generating authentication signatures which survive specific acceptable manipulations. In this paper, we present a novel approach which takes advantage of a multiscale framework and directionality to extract the significant features of an image from its redundant contourlet transform. The introduced redundancy brings simplicity and accuracy for feature calculation. We also describe the applied post-processing steps with the aim of stabilizing those features under acceptable image manipulations, namely lossy JPEG compression and additive noise corruption. Many experiments and comparative studies are performed to show the effectiveness of our technique in generating content signatures based on invariant image features, as well as to demonstrate its superiority when compared with a redundant wavelet approach.