Robustness Comparison Study on Watermarking Techniques against Compression Attack

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mohd Aliff Faiz Jeffry ◽  
Hazinah Kutty Mammi
Keyword(s):  
Social Media ◽  
Digital Watermarking ◽  
Digital Image ◽  
Comprehensive Analysis ◽  
Comparison Study ◽  
Compression Method ◽  
Designed Experiments ◽  
Network Bandwidth ◽  
And Storage ◽  
Stated Problem

Digital watermarking technique is a way of protecting digital image from malicious attacks. Compression attack is one of the most common attacks for images uploaded into social media. Social media, such as Facebook and Twitter, implement compression method for all types of media, before it is successfully uploaded into their server. This is to reduce the network bandwidth and storage needed to store each media in their server. However, the implemented compression method tends to tarnish image properties from the image itself, which can be used to identify the image itself. This produces other problems, which are ownership and copyright issues. Digital watermark has been proposed in numerous researches, and this research is one of them, in preventing the stated problem. The chosen digital watermarking techniques must be able to withstand against compression attack done by social media. A comprehensive analysis towards the watermarking algorithms and watermarked images were done, by applying several designed experiments. Based on the results, it shows that both chosen watermarking techniques could not withstands against compression attack made by JPEG compression and social media compression. It indicates that watermarking technique was not a suitable method to be used in preserving the ownership and copyright of the image throughout social media.

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

The specifics of mergers and acquisitions of innovative and technological companies

2020 ◽  
Vol 26 (5) ◽  
pp. 1186-1204
Author(s):  
A.V. Fedorov ◽  
Zh.S. Peredera
Keyword(s):  
Digital Technology ◽  
Comprehensive Analysis ◽  
Methodological Framework ◽  
Comparison Study ◽  
Technology Sector ◽  
Theoretical Perspectives ◽  
Innovation And Technology ◽  
Set Up ◽  
Definition Of ◽  
Traditional Approaches

Subject. The article reviews distinctions of M&A deals in innovation and technology. Objectives. We determine the specifics of innovative and technological companies and its impact on the synergy, process, finance, valuation of M&A deals. Methods. The article employs methods of generalization, comprehensive analysis, systematization, specification, comparison, study into trends and the structure. Graphics and tables are used to display the findings. Results. We conducted the content analysis of the term Mergers & Acquisitions, thus finding the divergence of foreign and the Russian approaches. We provide our own definition of the concept and analyzed the dynamics of the overall M&A market and the innovation and technological sector. The article describes operational distinctions of innovative and technological companies and compares them with conventional sectors. The article determined the specifics of synergy, process, finance, valuation of M&A deals in innovation and technology. Conclusions and Relevance. The innovation and technology sector saw M&A deals become more frequent for the recent five years. What distinguishes them is the number of startups and infant businesses, large M&A deals in order to develop their ecosystems, involve digital technology companies. Traditional approaches should be adapted for structuring M&A deals, their arrangement, financing and valuation of target companies. The findings can lay the groundwork for further studies into the specifics of the innovation and technology sector, M&A deals, and set up the methodological framework for the valuation of innovative and technological companies. The findings can also immediately support parties of M&A deals from theoretical perspectives.

scholarly journals Social Media Adoption, Usage And Impact In Business-To-Business (B2B) Context: A State-Of-The-Art Literature Review

2021 ◽  
Author(s):  
Yogesh K. Dwivedi ◽  
Elvira Ismagilova ◽  
Nripendra P. Rana ◽  
Ramakrishnan Raman
Keyword(s):  
Social Media ◽  
Media Use ◽  
State Of The Art ◽  
Relevant Literature ◽  
Comprehensive Analysis ◽  
Social Media Use ◽  
Weight Analysis ◽  
Social Media Tools ◽  
Use Of Social Media ◽  
Business To Business

AbstractSocial media plays an important part in the digital transformation of businesses. This research provides a comprehensive analysis of the use of social media by business-to-business (B2B) companies. The current study focuses on the number of aspects of social media such as the effect of social media, social media tools, social media use, adoption of social media use and its barriers, social media strategies, and measuring the effectiveness of use of social media. This research provides a valuable synthesis of the relevant literature on social media in B2B context by analysing, performing weight analysis and discussing the key findings from existing research on social media. The findings of this study can be used as an informative framework on social media for both, academic and practitioners.

Blind Digital Image Watermarking Algorithm Based on the Chain Code

2012 ◽  
Vol 546-547 ◽  
pp. 410-415
Author(s):  
Chun Ge Tang ◽  
Tie Sheng Fan ◽  
Lei Liu ◽  
Zhi Hui Li
Keyword(s):  
Image Quality ◽  
Digital Watermarking ◽  
Digital Image ◽  
Image Watermarking ◽  
Boundary Representation ◽  
Experimental Results ◽  
Digital Image Watermarking ◽  
Original Image ◽  
Chain Code ◽  
Decision Method

A new blind digital watermarking algorithm based on the chain code is proposed. The chain code is obtained by the characteristics of the original image -the edge contour. The feather can reflect the overall correlation of the vector image, and chain code expression can significantly reduce the boundary representation of the amount of data required. For the watermarking embedding, the original vector image is divided into sub-block images, and two bits of the watermarking information are embedded into sub-block images repeatedly by quantization. For watermarking extracting, the majority decision method is employed to determine the size of the extracted watermark. Experimental results show that the image quality is not significantly lowered after watermarking. The algorithm can resist the basic conventional attacks and has good robustness on the shear attacks.

Digital Image Zero-Watermarking Algorithm Based on Improved Wavelet Moment

2013 ◽  
Vol 347-350 ◽  
pp. 3232-3236
Author(s):  
Zheng Bao Zhang ◽  
Chao Jia
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Real Time ◽  
Digital Watermarking ◽  
Digital Image ◽  
Image Rotation ◽  
The Real ◽  
Geometric Attacks ◽  
Zero Watermarking ◽  
Local Distortions

Lots of anti-RST attacks watermarking algorithms have been proposed, but few solutions for local geometric attacks, in this paper it proposed a new algorithm combined with the the Wavelet Moment for an anti-geometric attacks. Since wavelet moment was proposed, it is widely used in the field of computer vision, image processing, but the large amount of computation must be improved to be applied to digital watermarking technology so that it can adapt to the real-time detection of digital watermarking. By image rotation, scaling, translation, shear, local distortions, filtering attack operations and so on, these attacks can be seen that the algorithm has good robustness, and the efficiency of watermark detection is relatively high. The experiments show that the algorithm is robustness, greatly accelerate the speed of operation, to unify the robust and efficient.

scholarly journals A note on precision-preserving compression of scientific data

2020 ◽  
Author(s):  
Rostislav Kouznetsov
Keyword(s):  
Numerical Data ◽  
Lossy Compression ◽  
Scientific Data ◽  
Essential Information ◽  
Network Bandwidth ◽  
Simple Implementation ◽  
Optimal Accuracy ◽  
Point Data ◽  
Multipoint Statistics ◽  
And Storage

Abstract. Lossy compression of scientific data arrays is a powerful tool to save network bandwidth and storage space. Properly applied lossy compression can reduce the size of a dataset by orders of magnitude keeping all essential information, whereas a wrong choice of lossy compression parameters leads to the loss of valuable data. The paper considers statistical properties of several lossy compression methods implemented in "NetCDF operators" (NCO), a popular tool for handling and transformation of numerical data in NetCDF format. We compare the effects of imprecisions and artifacts resulting from use of a lossy compression of floating-point data arrays. In particular, we show that a popular Bit Grooming algorithm (default in NCO) has sub-optimal accuracy and produces substantial artifacts in multipoint statistics. We suggest a simple implementation of two algorithms that are free from these artifacts and have twice higher precision. Besides that, we suggest a way to rectify the data already processed with Bit Grooming. The algorithm has been contributed to NCO mainstream. The supplementary material contains the implementation of the algorithm in Python 3.

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