Watermarking Techniques for DRM Applications

2009 ◽  
pp. 71-100
Author(s):  
Alessandro Piva ◽  
Roberto Caldelli ◽  
Alessia De Rosa ◽  
Mauro Barni ◽  
Vito Cappellini
Keyword(s):  
Digital Watermarking ◽  
Digital Image ◽  
Spread Spectrum ◽  
Image Watermarking ◽  
Mathematical Formulation ◽  
Multimedia Content ◽  
Practical Implementation ◽  
Digital Image Watermarking ◽  
Spread Spectrum Watermarking ◽  
Watermarking Scheme

The need to safeguard the property rights of multimedia content from unauthorized copying and the possibility to determine the true owners of the asset can be faced by resorting to efficient digital watermarking systems. This chapter presents a mathematical formulation to define a digital watermarking system and describes the general requirements to be satisfied, with more emphasis given to the aspects of security, robustness, and imperceptibility. After this general discussion, the two main classes of digital watermarking schemes, namely the spread-spectrum watermarking and the side-informed watermarking are explained by highlighting their main advantages and drawbacks. This analysis is completed by the description of a practical implementation of a digital image watermarking scheme. Finally, the use of watermarking systems in the framework of a DRM is deeply analyzed.

On the Implementation of a Digital Image Watermarking Framework Using Saliency and Phase Congruency

2017 ◽  
pp. 253-292
Author(s):  
Abhishek Basu ◽  
Susmita Talukdar
Keyword(s):  
Data Hiding ◽  
Digital Image ◽  
Image Watermarking ◽  
Saliency Map ◽  
Digital Image Watermarking ◽  
Phase Congruency ◽  
Hiding Capacity ◽  
Spectral Residual ◽  
Watermarking Scheme ◽  
Least Significant Bits

In this paper, a saliency and phase congruency based digital image watermarking scheme has been projected. The planned technique implants data at least significant bits (LSBs) by means of adaptive replacement. Here more information is embedded into less perceptive areas within the original image determined by a combination of spectral residual saliency map and phase congruency map. The position of pixels with less perceptibility denotes the most unimportant region for data hiding from the point of visibility within an image. Therefore any modification within these regions will be less perceptible to one observer. The model gives a concept of the areas which has excellent data hiding capacity within an image. Superiority of the algorithm is tested through imperceptibility, robustness, along with data hiding capacity.

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