Data Embedding for Covert Communications, Digital Watermarking, and Information Augmentation

2000 ◽  
Author(s):  
Arnold C. Baldoza
Keyword(s):  
Digital Watermarking ◽  
Data Embedding ◽  
Covert Communications

Security Method for Multimedia Content by Using Watermarking

2014 ◽  
Vol 626 ◽  
pp. 1-6
Author(s):  
R. Kavitha ◽  
B. Arivuselvam ◽  
G. Anand
Keyword(s):  
Empirical Mode Decomposition ◽  
Digital Watermarking ◽  
Copyright Protection ◽  
Additive Noise ◽  
Video Watermarking ◽  
Multimedia Content ◽  
Digital Audio ◽  
Data Embedding ◽  
Mode Decomposition ◽  
Embedding Rate

Digital watermarking is a technique developed to help copyright protection of Image, audio & video files. It has been spurred by the growth of the Internet, and the ease of copying. This has led to an unprecedented numbers in copyright infringements. The digital audio & video watermarking is concerned with embedding data in a signal the watermark data can be accurately detected. Watermarking algorithm based on Empirical Mode Decomposition (EMD) is introduced. The signal is divided into frames and each one is decomposed adaptively by Empirical Mode Decomposition into intrinsic oscillatory components. The data embedding rate of EMD algorithm is 46.9-50.3 b/s; the robustness of hidden watermark is identified using Mp3 compression, additive noise, and quantization, cropping, filtering and resampling.

Digital Watermarking – A Multidisciplinary Approach

2013 ◽  
Vol 5 (1) ◽  
pp. 18-23
Author(s):  
L. Venkateswarlu ◽  
◽  
Dr. N V Rao ◽  
Keyword(s):  
Digital Watermarking ◽  
Multidisciplinary Approach

A Method of Data Embedding and Extracting for Information Retrieval Considering Mobile Devices

2013 ◽  
Vol E96.A (6) ◽  
pp. 1214-1221 ◽  
Author(s):  
Mitsuji MUNEYASU ◽  
Hiroshi KUDO ◽  
Takafumi SHONO ◽  
Yoshiko HANADA
Keyword(s):  
Information Retrieval ◽  
Mobile Devices ◽  
Data Embedding

Video Data Embedding. Part II

2013 ◽  
Vol 45 (4) ◽  
pp. 75-83
Author(s):  
Lyubov L. Nikitenko
Keyword(s):  
Video Data ◽  
Data Embedding

Robust Multispectral Data Hiding in RGB Image Using Digital Watermarking

2016 ◽  
Vol 2016 (1) ◽  
pp. 213-218
Author(s):  
Kazushige Banzawa ◽  
Kazuma Shinoda ◽  
Madoka Hasegawa
Keyword(s):  
Digital Watermarking ◽  
Data Hiding ◽  
Multispectral Data ◽  
Rgb Image

Evaluvation of Multiresolution Watermarking Algorithm

2017 ◽  
Vol 7 (8) ◽  
pp. 85
Author(s):  
S. Thabasu Kannan ◽  
S. Azhagu Senthil
Keyword(s):  
Digital Watermarking ◽  
Wavelet Transformation ◽  
Signal To Noise Ratio ◽  
Rapid Development ◽  
Threshold Value ◽  
Discrete Wavelet ◽  
Digital Production ◽  
Common Framework ◽  
Sampling Operation ◽  
Watermarking Scheme

Now-a-days watermarking plays a pivotal role in most of the industries for providing security to their own as well as hired or leased data. This paper its main aim is to study the multiresolution watermarking algorithms and also choosing the effective and efficient one for improving the resistance in data compression. Computational savings from such a multiresolution watermarking framework is obvious. The multiresolutional property makes our watermarking scheme robust to image/video down sampling operation by a power of two in either space or time. There is no common framework for multiresolutional digital watermarking of both images and video. A multiresolution watermarking based on the wavelet transformation is selected in each frequency band of the Discrete Wavelet Transform (DWT) domain and therefore it can resist the destruction of image processing.   The rapid development of Internet introduces a new set of challenging problems regarding security. One of the most significant problems is to prevent unauthorized copying of digital production from distribution. Digital watermarking has provided a powerful way to claim intellectual protection. We proposed an idea for enhancing the robustness of extracted watermarks. Watermark can be treated as a transmitted signal, while the destruction from attackers is regarded as a noisy distortion in channel.  For the implementation, we have used minimum nine coordinate positions. The watermarking algorithms to be taken for this study are Corvi algorithm and Wang algorithm. In all graph, we have plotted X axis as peak signal to noise ratio (PSNR) and y axis as Correlation with original watermark. The threshold value ά is set to 5. The result is smaller than the threshold value then it is feasible, otherwise it is not.

Digital Watermarking

2017 ◽  
Vol 7 (6) ◽  
pp. 141-143
Author(s):  
Matthew N.O. Sadiku ◽  
◽  
Adebowale E. Shadare ◽  
Sarhan M. Musa ◽  
◽  
...  
Keyword(s):  
Digital Watermarking
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