Markov chaotic sequences for correlation based watermarking schemes

In this paper, statistical analysis of watermarking schemes based on correlation detection is presented. Statistical properties of watermark sequences generated by piecewise-linear Markov maps are exploited, resulting in superior watermark detection reliability. Correlation/spectral properties of such sequences are easily controllable, a fact that affects the watermarking system performance. A family of chaotic maps, namely the skew tent map family, is proposed for use in watermarking schemes.