NDLI: An Adaptive Watermark Scheme Based on Contourlet Transform

Content Provider	IEEE Xplore Digital Library
Author	Feng Wei Tong Ming Ji Hong-bing
Copyright Year	2008
Description	Author affiliation: Sch. of Electron. Eng., Xidian Univ., Xian, China (Feng Wei; Tong Ming; Ji Hong-bing)
Abstract	Based on the convergence and stability of the new mean shift fast algorithm, an adaptive watermark algorithm in contourlet domain based on mean shift texture features clustering is proposed in this paper. Through the texture recognition method based on gray co-occurrence matrix, watermark is embedded into the coefficients in contourlet domain, which makes the capability of the watermark more covert, anti-noise attack and robust. During the clustering, three texture features including energy, entropy and contrast were selected for mean shift fast clustering algorithm. Strong regional textures of host images are extracted directly, accurately and efficiently, and the embedding intensity can be gain automatically then. The experiment shows that this algorithm has the strong robustness to Gauss low pass filter, Wiener filter, median filtering, Salt and pepper noise, Gaussian noise, JPEG compression, shear attack etc. It is a blind detection, and adapt to various of images.
Starting Page	677
Ending Page	681
File Size	305678
Page Count	5
File Format	PDF
ISBN	9781424437467
DOI	10.1109/ISCSCT.2008.174
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stability Low pass filters Watermarking Entropy Blind Watermark Mean Shift Clustering Algorithm Gray Co-occurrence Matrix Convergence Wiener filter Gaussian noise Clustering algorithms Contourlet Transform Domain Filtering algorithms Robustness
Content Type	Text
Resource Type	Article

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