Multibit decoding of multiplicative watermarking for fingerprint images

Khalil Zebbiche; Fouad Khelifi; Ahmed Bouridane

Multibit decoding of multiplicative watermarking for fingerprint images

Khalil Zebbiche, Fouad Khelifi, Ahmed Bouridane

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
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
Externally published	Yes

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title = "Multibit decoding of multiplicative watermarking for fingerprint images",

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.",

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AU - Zebbiche, Khalil

AU - Khelifi, Fouad

AU - Bouridane, Ahmed

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Y1 - 2007/7/1

N2 - 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.

AB - 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.

M3 - Conference contribution

BT - In the proceedings of the IET International Conference on Visual Information Engineering (VIE 2007)

ER -

Multibit decoding of multiplicative watermarking for fingerprint images

Abstract

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