NDLI: Steganography of Digital Watermark Based on Artificial Neural Networks in Image Communication and Intellectual Property Protection

Content Provider	Springer Nature Link
Author	Yu, Chong
Copyright Year	2015
Abstract	In this paper, a novel steganography of digital watermark scheme which contains digital watermark embedding and extraction processes is proposed. The proposed scheme is based on an iterative process of Arnold scrambling transform which is controlled by secret key shared by copyright owner and authorized users, and the extension of morphological component analysis theory which utilizes morphological diversity as the kernel role in blind source separation. This scheme overcomes the problem of too narrow hidden data bandwidth in traditional LSB replacement or LSB matching schemes. Compared with classic JPEG steganography schemes, the proposed scheme has much higher embedding capacity and broader applicability scope. Images acquired in experiments and the analysis of experimental results both prove the effectiveness of proposed scheme. Objective quantitative results of the peak signal to noise ratio, structural similarity, and normalized correlation indices confirm its brilliant steganography capability as well as its fine robustness to different noise attacks through communication channel.
Starting Page	307
Ending Page	316
Page Count	10
File Format	PDF
ISSN	13704621
Journal	Neural Processing Letters
Volume Number	44
Issue Number	2
e-ISSN	1573773X
Language	English
Publisher	Springer US
Publisher Date	2015-08-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Arnold scrambling transform Blind source separation Digital watermark Morphological component analysis Secret key Steganography Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity Computational Intelligence
Content Type	Text
Resource Type	Article
Subject	Neuroscience Artificial Intelligence Computer Networks and Communications Software

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