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

Khalil Zebbiche, Fouad Khelifi

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)23-32
JournalIET Image Processing
Issue number1
Publication statusPublished - Jan 2014


Dive into the research topics of 'Efficient wavelet-based perceptual watermark masking for robust fingerprint image watermarking'. Together they form a unique fingerprint.

Cite this