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Content Provider | IET Digital Library |
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Author | Zebbiche, Khalil Khelifi, Fouad |
Abstract | 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. |
Starting Page | 23 |
Ending Page | 32 |
Page Count | 10 |
ISSN | 17519659 |
Volume Number | 8 |
e-ISSN | 17519667 |
Issue Number | Issue 1, Jan (2014) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/8/1 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2013.0055 |
Journal | IET Image Processing |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Brightness Masking Computer Vision And Image Processing Technique Human Visual System Characteristic Image And Video Coding Image Enhancement Image Texture Image Watermarking Imperceptibility Integral Transforms JPW Model Just Perceptual Weighting Model Robust Wavelet-based Fingerprint Image Watermarking Scheme Spatial Frequency Sensitivity Texture Masking Wavelet Transform Wavelet-based Perceptual Watermark Masking |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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