Khalil Zebbiche

Protecting Fingerprint Data Using Watermarking

A motivation for the use of watermarking techniques in biometric systems has been the need to provide increased security to the biometrics data themselves. We introduce an application of wavelet-based watermarking method to hide the fingerprint minutiae data in fingerprint images. The application provides a high security to both hidden data (i.e. fingerprint minutiae) that have to be transmitted and the host image (i.e. fingerprint). The original unmarked fingerprint image is not required to extract the minutiae data. The method is essentially introduced to increase the security of fingerprint minutiae transmission and can also used to protect the original fingerprint image

Region-Based Watermarking of Biometric Images: Case Study in Fingerprint Images

In this paper, a novel scheme to watermark biometric images is proposed. It exploits the fact that biometric images, normally, have one region of interest, which represents the relevant part of information processable by most of the biometric-based identification/authentication systems. This proposed scheme consists of embedding the watermark into the region of interest only; thus, preserving the hidden data from the segmentation process that removes the useless background and keeps the region of interest unaltered; a process which can be used by an attacker as a cropping attack. Also, it provides more robustness and better imperceptibility of the embedded watermark. The proposed scheme is introduced into the optimum watermark detection in order to improve its performance. It is applied to fingerprint images, one of the most widely used and studied biometric data. The watermarking is assessed in two well-known transform domains: the discrete wavelet transform (DWT) and the discrete Fourier transform (DFT). The results obtained are very attractive and clearly show significant improvements when compared to the standard technique, which operates on the whole image. The results also reveal that the segmentation (cropping) attack does not affect the performance of the proposed technique, which also shows more robustness against other common attacks.

An Efficient Watermarking Technique for the Protection of Fingerprint Images

This paper describes an efficient watermarking technique for use to protect fingerprint images. The rationale is to embed the watermarks into the ridges area of the fingerprint images so that the technique is inherently robust, yields imperceptible watermarks, and resists well against cropping and/or segmentation attacks. The proposed technique improves the performance of optimum multibit watermark decoding, based on the maximum likelihood scheme and the statistical properties of the host data. The technique has been applied successfully on the well-known transform domains: discrete cosine transform (DCT) and discrete wavelet transform (DWT). The statistical properties of the coefficients from the two transforms are modeled by a generalized Gaussian model, widely adopted in the literature. The results obtained are very attractive and clearly show significant improvements when compared to the conventional technique, which operates on the whole image. Also, the results suggest that the segmentation (cropping) attack does not affect the performance of the proposed technique, which also provides more robustness against other common attacks.

Efficient wavelet-based perceptual watermark masking for robust fingerprint image watermarking

In this study, a robust wavelet-based fingerprint image watermarking scheme using an efficient just perceptual weighting (JPW) model has been proposed. The JPW model exploits three human visual system characteristics, namely: spatial frequency sensitivity, local brightness masking and texture masking, to compute a weight for each wavelet coefficient, which is then used to control the amplitude of the inserted watermark. The idea is motivated by the fact that fingerprint images perceptually differ from natural images and a JPW model adapted to such images would further enhance the robustness of the watermarking scheme. Experimental results show that the proposed model significantly improves the performance of the conventional watermarking technique in terms of robustness while maintaining the same imperceptibility of the watermark. Finally, the proposed technique has shown a clear superiority over a number of related state-of-the-art masking techniques.

Optimum detection of multiplicative-multibit watermarking for fingerprint images

Watermarking is an attractive technique which can be used to ensure the security and the integrity of fingerprint images. This paper addresses the problem of optimum detection of multibit, multiplicative watermarks embedded within Generalized Gaussian distribution features in Discrete Wavelet Transform of fingerprint images. The structure of the proposed detector has been derived using the maximum-likelihood approach and the Neyman-Pearson criterion. The parameters of the Generalized Gaussian distribution are directly estimated from the watermarked image, which makes the detector more suitable for real applications. The performance of the detector is tested by taking into account the different quality of fingerprint images and different attacks. The results obtained are very attractive and the watermark can be detected with low detection error. Also, the results reveal that the proposed detector is more suitable for fingerprint images with good visual quality.

Robust Multibit Decoding and Detection of Multiplicative Watermarks for Fingerprint Images

In this paper, multibit watermark decoding and detection structures of fingerprint images are proposed. The watermark is hidden within the high frequencies coeffi- cients of the discrete wavelet transform (DWT) which are statistically modeled by generalized Gaussian distribution. The structure of the decoder and the detector are based on the maximum-likelihood (ML) method. For flexibility purposes, the original image is not necessary during the decoding and the detection processes. Analytical expressions for performance measures such as the probability of error in watermark decoding and probabilities of false alarm and detection in watermark detection are derived and contrasted with experimental results. The results obtained are very attractive when considering a number of commonly used attacks and the proposed detector and decoder have been shown to outperform similar detectors/decoders existing in the literature. They also show that the overall performances of both decoder and detector are dependent on the fingerprint image characteristics, namely, on the size of the ridges area relative to the size of the fingerprint image.

Efficient Joint Watermarking and WSQ Compression Scheme

In this paper, an efficient joint watermarking and Wavelet Scalar Quantization (WSQ) compression scheme based on Quantization Index Modulation (QIM) watermarking approach is proposed to attenuate the impact of the compression operation on the embedded watermark. The proposed scheme allows the embedding of secret message directly into the fingerprint data when compressed by the WSQ algorithm. Experimental results have shown the robustness of the proposed scheme against the WSQ compression while slightly affecting its compression performance (i.e. visual quality and compression rate).

Robust Additive Watermarking in the DTCWT Domain Based on Perceptual Masking

In this paper, a robust additive image watermarking system operating in the Dual Tree Complex Wavelet Transform (DTCWT) domain is proposed. The system takes advantage of a new perceptual masking model that exploits the Human Visual System (HVS) characteristics at the embedding stage. It also uses an efficient watermark detection structure, called the Rao-test, to verify the presence of the candidate watermark. This structure relies on the statistical modeling of high frequency DTCWT coefficients by the Generalized Gaussian distribution. Experimental results show that the proposed system outperforms related state-of-the-art watermarking systems in terms of imperceptibility and robustness.