In this paper, we propose an optimum decoder of multibit, multiplicative watermarks hidden within discrete wavelet transform (DWT) coefficients of fingerprint images. The structure of the decoder is based on the maximum-likelihood (ML) method which requires a probability distribution function (PDF). Generalized Gaussian PDF is used to model the statistical behaviour of the DWT coefficients. The performance of the decoder is tested in realistic scenarios, where attacks are taken into account. The experiments reveal that the proposed decoder provides very attractive results and the decoding error is within an acceptable range of tolerance.
|Title of host publication||In the proceedings of the IET International Conference on Visual Information Engineering (VIE 2007)|
|Number of pages||5|
|Publication status||Published - 1 Jul 2007|