NDLI: Regression of SVM based robust watermarking algorithm

Content Provider	IEEE Xplore Digital Library
Author	Fuxin Wang Wei Song Jianjun Hou
Copyright Year	2008
Description	Author affiliation: Hebi Coll. of Vocation & Technol., Hebi (Fuxin Wang) \|\| Sch. of Electron. & Inf. Eng., Beijing Jiaotong Univ., Beijing (Wei Song; Jianjun Hou)
Abstract	This paper presents a robust watermarking algorithm based on regression of SVM. The host image is divided into two parts firstly. The first one is to train SVM using features including four relationships between the neighbor pixels, and the other part is to embed watermarks. The center pixels of image blocks are compared with the predicted pixels of trained SVM, and then modified to embed watermarks. Because of the introduction of Pseudorandom Circular Chain (PCC) scheme, the training pixels and the test pixels can spread all over the host image, which increases accurate rate of the watermark-extraction. Otherwise, for the security consideration, logistic mapping is used to permute the watermark image. Experiment results demonstrate that this algorithm can get good perceptual invisibility, and robustness against many attacks.
Starting Page	2197
Ending Page	2200
File Size	251766
Page Count	4
File Format	PDF
ISBN	9781424421787
DOI	10.1109/ICOSP.2008.4697584
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Robustness Watermarking Pixel Support vector machine classification Intellectual property Resists Educational institutions Testing Security Pseudorandom Circular Chain (PCC) Digital Watermarks Support Vector Machines (SVM)
Content Type	Text
Resource Type	Article

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