Multibit Decoding of Multiplicative Watermarking for Fingerprint Images K.Zebbiche, F.Khelifi, A.Bouridane School of Electronics, Electrical Engineering and Computer Science Queen’s University Belfast Belfast,BT7 1NN Email: {kzebbiche01, fkhelifi01, A.Bouridane}@qub.ac.uk Keywords: Multibit decoding, Multiplicative watermark, Maximum-likelihood. Abstract 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. 1 Introduction With the widespread utilisation of fingerprint-based identification systems, establishing the authenticity of fingerprint data itself has emerged as an important research issue. Watermarking is a possible technique that can be used to increase the security of the fingerprint images [8] and may be used in applications like protecting the originality of fingerprint images stored in databases against intentional and unintentional attacks, fraud detection, guaranteeing secure transmission of acquired fingerprint images from intelligence agencies to a central database,…etc. Watermarking is defined as embedding information such as ID, origin, destination, access level,…etc in the host data. The embedded information may be recovered later on and used to check the authenticity of the host data. Two processes can be defined at this stage: (i) the detection stage, which aims to decide whether a given watermark has been inserted in the host image, referred to as one-bit watermark detection, and (ii) given that a watermark is embedded into the host image, the decoding aims to extract bit by bit the hidden information, referred to as multibit watermarking decoding. In practice, since a watermarked image is altered by several attacks, the hidden information cannot be completely extracted and errors may occur, thus a good decoder should be able to estimate the hidden information with a low probability of error. Optimum decoding of multibit watermark has been proposed in [2, 5, 6]. Hernandez et al. [5, 6] proposed an optimum multibit decoder for image watermarking operating in the discrete cosine transform (DCT) domain and used Generalized Gaussian PDF to model the distribution of the DCT coefficients. However, this decoding scheme refers to the additive watermarking and thus cannot be applied when a different embedding rule is used. Barni et al. [2] proposed an optimum decoding and detecting technique for a multibit, multiplicative watermark hosted in the magnitude-of-DFT domain, modelled by Weibull distribution. In this work, we propose an optimum decoding of a multibit, multiplicative watermark embedded in the DWT coefficients of fingerprint images. By assuming equally probable information bits, optimum decoding is considered as a maximum-likelihood (ML) estimation scheme which allows the derivation of the structure of the decoder based on the parametric model of the PDF of the DWT coefficients. A Generalized Gaussian PDF is used to model the statistical behaviour of the coefficients. The performance of the proposed decoder is examined through a number of experiments using real fingerprint images with different quality to derive the error of decoding probability. We have also used the Bose–Chaudhuri–Hochquenghem (BCH) code [3, 7] to increase the successful rate of decoding. Further experimentations have been carried out to assess the performance of the decoder in more realistic scenarios, where different attacks are taken into account. The rest of the paper is organized as follows: Section 2 explains how the watermark is embedded within DWT coefficients. The optimum decoder is derived for the Generalised Gaussian distribution as described in section 3 while the experimental results are provided in Section 4. The conclusion is presented in Section 5. 2 Information encoding and watermark casting The multibit watermarking technique presented here is an extension of the one-bit watermarking scheme developed in [1]. The watermark is embedded into the DWT subbands coefficients. Let b= {b 1 …b Nb } be the information bit sequence to be hidden (assuming value +1 for bit 1 and -1 for bit 0) and m= {m 1 m 2 …m N } a pseudo-random set uniformly distributed in [-1, 1], which is generated using a secret key K. The information bits b are hidden as follows: (i) the DWT subband coefficients used to carry the watermark are partitioned into N b non-overlapping blocks {B i : 1 ≤ i ≤ N n }. (ii) the watermark sequence m is split into N b non-overlap chunks {M i : 1≤ i ≤ N n } (where the number of elements in B k is equal to the number of elements in chunk M k ), so that, each block B k and each chunk M k will be used to carry one