1) The document proposes a hybrid digital watermarking scheme that uses both discrete wavelet transform (DWT) and singular value decomposition (SVD) for color image authentication.
2) In the proposed scheme, the watermark is embedded in the singular values of the DWT sub-bands of the cover image, rather than directly on the wavelet coefficients. This reduces computational expense compared to other DWT-SVD methods.
3) Experimental results on test images show that the hybrid DWT-SVD scheme provides better imperceptibility and robustness against various attacks compared to using DWT or SVD alone. The recovered watermarks had high quality even after the watermarked images were distorted.
A Quick Glance over the Digital Watermarkingijsrd.com
Digital watermarking is a process for modifying physical or electronic media to embed a machine-readable code into the media. The media may be modified such that the embedded code is imperceptible or nearly imperceptible to the user, yet may be detected through an automated detection process. Watermarking is the art of imperceptibly embedding a message into a work. More than 700 years ago in Fabriano (Italy), paper watermarks appeared in handmade paper, in order to identify its provenance, format, and quality. In this context, the watermark is a kind of invisible signature that allows identifying the creator or the owner of a document, and to detect possible copyright violations, and especially non-authorized copying [1]. More recently, different watermarking techniques and strategies have been proposed in order to solve a number of problems, ranging from the detection of content manipulations, to information hiding (steganography), to document usage tracing. In particular, the insertion of multiple watermarks to trace a document during its lifecycle is a very interesting and challenging application [1]. The main property of the proposed method is that it allows the insertion of multiple watermarks by different users, who sequentially come into play one after the other and do not need any extra information besides the public keys. This characteristic makes the present approach more attractive than previously available solutions.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Quick Glance over the Digital Watermarkingijsrd.com
Digital watermarking is a process for modifying physical or electronic media to embed a machine-readable code into the media. The media may be modified such that the embedded code is imperceptible or nearly imperceptible to the user, yet may be detected through an automated detection process. Watermarking is the art of imperceptibly embedding a message into a work. More than 700 years ago in Fabriano (Italy), paper watermarks appeared in handmade paper, in order to identify its provenance, format, and quality. In this context, the watermark is a kind of invisible signature that allows identifying the creator or the owner of a document, and to detect possible copyright violations, and especially non-authorized copying [1]. More recently, different watermarking techniques and strategies have been proposed in order to solve a number of problems, ranging from the detection of content manipulations, to information hiding (steganography), to document usage tracing. In particular, the insertion of multiple watermarks to trace a document during its lifecycle is a very interesting and challenging application [1]. The main property of the proposed method is that it allows the insertion of multiple watermarks by different users, who sequentially come into play one after the other and do not need any extra information besides the public keys. This characteristic makes the present approach more attractive than previously available solutions.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
it is used for security purpose using two level dct and wavelet packet denoising .based on digital image processing.the software based on matlab.it is used for high security purpose.
In this era any type of digital media such as image, text, audio and video, all are easily accessible and transferable through the use of high speed internet. As the use of internet increased, the need of security and authenticity also increased. To secure the multimedia data such as image, audio, text and video researcher has developed a watermarking technique which gives a watermark embedding and watermark extraction algorithm, and later it is used for proof of ownership. Here we are proposing a technique on video watermarking using 2D DWT and 2-level SVD technique. In this paper first we are taking a video which is decomposed into number of frames and embedding a watermark image on each frame. First 2-D DWT is applied on each frame. Dwt decompose each frame into low frequency, mid frequency and in high frequency (LL, LH, HL, HH) band then we applied SVD on LL and HL sub-band called it dual band. SVD convert it into three matrices as U1S1V1’ of single matrix. A watermark image is taken which converted in to gray scale from RGB scale then resized it. And embed this watermark image into host frames with some scaling factor. After that we again applied SVD on this watermarked frames which further convert this single matrix into three matrices as U2S2V2’ now multiply S2 matrix with U1 and V1 matrix component to make it more secure. To demonstrate the authenticity of this watermarked video we applied some attacks such as Gaussian filtering, median filtering, frame rotation, contrast adjustment and sharpness attack which show its PSNR and NCC value in comparison with the original video.
A Brief Survey on Robust Video Watermarking Techniquestheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
This presentation features definition of watermarking, its applications, methods to implement a visible and invisible watermark and the possible attacks on watermark.
Performance Comparison of Digital Image Watermarking Techniques: A SurveyEditor IJCATR
Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image,
which is overlaid on the host image, and provides a means of protecting the image. In order to provide high quality watermarked
image, the watermarked image should be imperceptible. This paper presents different techniques of digital image watermarking based
on spatial & frequency domain, which shows that spatial domain technique provides security & successful recovery of watermark
image and higher PSNR value compared to frequency domain.
helping users to embed images in other images to maintain the integrity of the images being transferred. Watermarking is one technique through which we can accomplish this. Here we are using few algorithms, like Least Significant Bit ,Wavelet Image Watermarking , DCT Image watermarking and FFT Image watermarking. Our aim was to study different watermarking techniques and implement the one which is most resistant to all types of attack, scalar or geometric.
it is used for security purpose using two level dct and wavelet packet denoising .based on digital image processing.the software based on matlab.it is used for high security purpose.
In this era any type of digital media such as image, text, audio and video, all are easily accessible and transferable through the use of high speed internet. As the use of internet increased, the need of security and authenticity also increased. To secure the multimedia data such as image, audio, text and video researcher has developed a watermarking technique which gives a watermark embedding and watermark extraction algorithm, and later it is used for proof of ownership. Here we are proposing a technique on video watermarking using 2D DWT and 2-level SVD technique. In this paper first we are taking a video which is decomposed into number of frames and embedding a watermark image on each frame. First 2-D DWT is applied on each frame. Dwt decompose each frame into low frequency, mid frequency and in high frequency (LL, LH, HL, HH) band then we applied SVD on LL and HL sub-band called it dual band. SVD convert it into three matrices as U1S1V1’ of single matrix. A watermark image is taken which converted in to gray scale from RGB scale then resized it. And embed this watermark image into host frames with some scaling factor. After that we again applied SVD on this watermarked frames which further convert this single matrix into three matrices as U2S2V2’ now multiply S2 matrix with U1 and V1 matrix component to make it more secure. To demonstrate the authenticity of this watermarked video we applied some attacks such as Gaussian filtering, median filtering, frame rotation, contrast adjustment and sharpness attack which show its PSNR and NCC value in comparison with the original video.
A Brief Survey on Robust Video Watermarking Techniquestheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
This presentation features definition of watermarking, its applications, methods to implement a visible and invisible watermark and the possible attacks on watermark.
Performance Comparison of Digital Image Watermarking Techniques: A SurveyEditor IJCATR
Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image,
which is overlaid on the host image, and provides a means of protecting the image. In order to provide high quality watermarked
image, the watermarked image should be imperceptible. This paper presents different techniques of digital image watermarking based
on spatial & frequency domain, which shows that spatial domain technique provides security & successful recovery of watermark
image and higher PSNR value compared to frequency domain.
helping users to embed images in other images to maintain the integrity of the images being transferred. Watermarking is one technique through which we can accomplish this. Here we are using few algorithms, like Least Significant Bit ,Wavelet Image Watermarking , DCT Image watermarking and FFT Image watermarking. Our aim was to study different watermarking techniques and implement the one which is most resistant to all types of attack, scalar or geometric.
Video Encryption and Decryption with Authentication using Artificial Neural N...IOSR Journals
Abstract :Multimedia data security is becoming important with the continuous increase of digital communications on internet. With the rapid development of various multimedia technologies, more and more multimedia data are generated and transmitted in the medical, commercial, and military fields, which may include some sensitive information which should not be accessed by or can only be partially exposed to the general users. . The encryption algorithms developed to secure text data are not suitable for multimedia application because of the large data size and real time constraint. Therefore, there is a great demand for secured data storage and transmission techniques. Information security has traditionally been ensured with data encryption and authentication techniques. The secrecy of communication is maintained by secret key exchange. In effect the strength of the algorithm depends solely on the length of the key. The presented work aims at secure video transmission using randomness in encryption algorithm, thereby creating more confusion to obtain the original data. The security of the original cipher has been enhanced by addition of impurities to misguide the cryptanalyst. Since the encryption process is one way function, the artificial neural networks are best suited for this purpose as they possess features like high security, no distortion and its ability to perform for non linear input-output characteristics, In the presented work the need for key exchange is also eliminated, which is otherwise a perquisite for most of the algorithms used today. The proposed work finds its application in medical imaging systems, military image database communication and confidential video conferencing, and similar such application. The results are obtained through the use of MATLAB 7.14.0 Keywords: Artificial Neural networks, Back propagation algorithm, video encryption and decryption, cipher and decipher.
Effect of Regular Exercise on Prolactin Secretion: A Pilot StudyIOSR Journals
Abstract:
Introduction: Evidence suggested that exercise may affects release of prolactin hormone. Participation in
exercise may increase secretion of prolactin hormone and may give sharp decrease in secretion of prolactin and
not only that published work demanded that there is no effect of exercise on secretion of prolactin. In this
context the researcher intend to know whether exercise affects positively or negatively or not on the release of
prolactin hormone. Aim: Determine whether participation in exercise may increase the level of secretion of
prolactine hormone or not. Method: Only two female students 29 years aged were participated in this study.
They were regularly practiced yogic asana and pranayam for 1 hour per day in the evening, 6 days per week,
for 8 weeks. The level of prolactin hormone was assessed by CLI method. In the present study all the
measurements were done at the baseline and 8 weeks of exercise training. Simple percentage calculated from
the mean value to see the quantitative changes in secretion of prolactin due to participation in the exercise
training. Result: Pre test mean was 5.80 and post test mean was 17.63 which imply that 203.96% increase in
secretion of prolactin significantly. Discussion and Conclusion: Level of secretion increased may be due to
multiple neural pathways that influence PRL secretion converges on the hypothalamus from other parts of the
brain; the effect of exercise on the secretion of PRL may also reflect the action of different neural inputs on the
activity of the hypothalamic–pituitary axis.
Key word: Exercise; Prolactin.
Monitoring Of Macronutrients Uptake by Soil and Potato Plants – A Comparative...IOSR Journals
Soil test1, 2 is necessary to identify optimal concentrations of essential elements required for plant growth. The fertility of soil is affected by the presence of some essential elements as Macronutrients like N, P& K. This study including the status of Macronutrients in the soil and potato plans. The percentage of nitrogen (N) in soil of potato plant was obtained 5.6% and 1.89% where as nitrogen percentage in plant ash was 17.45% and 16.4% respectively. But the phosphorus and potassium are present in adequate amount in soil. As it was found that the concentration of phosphorus (P) and potassium (K) in part per million in soil of potato was 62ppm and 148.3ppm and in potato plant ash the concentration was 64.23ppm and 103.3ppm respectively.
Fluorescence technique involves the optical detection and spectral analysis of light emitted by a substance undergoing a transition from an excited electronic state to a lower electronic state. The aim of this study is to assess the -amino levulinic acid (-ALA) uptake. Based on image processing technique, Matlab was used to analyze the fluorescence images resulted from activation of (-ALA) and follow its uptake along one week. Analyzing the RGB colours pixel profile from obtained results showed different profiles for malignant tissues, normal tissues, treated just after PDT and finally at one week post PDT. The treated tissues fluorescence profile showed changes from closer to malignant tissue profile till been closed to normal one.
Molecular characterization of pea (Pisum sativum L.) using microsatellite mar...IOSR Journals
Nineteen pea (Pisum sativum L.) accessions have been characterized using Simple Sequence Repeats (SSRs). The mains objectives of this study were to examine SSR polymorphism among cultivars and to assess genetic diversity among them. Eight microsatellites, from the Pisum microsatellite consortium (Agrogene ®, France) have been used. Five of the eight SSRs studied gave good electrophoretic profiles and helped us to amplify a number of alleles per locus varying from 3 (PSMPA5 and PSMPA6) to 13 (PSMPSAD126) with a total of 34 and an average number of 6.8 alleles per locus. The Polymorphism Information Content (PIC) varied from 0.18 for PSMPSAD134 to 0.85 for PSMPSAD126, with an average value of 0.62. The five microsatellites analyzed allowed us to separate 18 out of the 19 genotypes studied, and only the two most polymorphic markers (PSMPSAA205 and PSMPSAD126), permit to discriminate among the same genotypes (18) separated using the 5 SSRs. Genetic distances computed have been used to draw the corresponding dendrogram and to distribute genotypes according to their genetic relationship. The genotypes classified within the same group share several agro-morphological characters. Finally, the present study attests that SSR microsatellites are good tools for identifying genotypes and for the assessment of genetic diversity in pea.
A Review on Robust Digital Watermarking based on different Methods and its Ap...IJSRD
Digital Watermarking is the process of embedding data called watermark or signature or label or tag into a multimedia object (image or audio or video) so that the watermark can be extracted for ownership verification or authentication. A visible watermark is a secondary translucent image overlaid into the primary image and appears visible to a viewer on a careful inspection. The invisible watermark is embedded in such a way that the modification made to the pixel value is perceptually not noticed and it can be recovered only with an appropriate decoding mechanism. Digital watermarking is used to hide the information inside a signal, which cannot be easily extracted by the third party. Its widely used application is copyright protection of digital information. It is different from the encryption in the sense that it allows the user to access, view and interpret the signal but protect the ownership of the content. One of the current research areas is to protect digital watermark inside the information so that ownership of the information cannot be claimed by third party.
A New Technique to Digital Image Watermarking Using DWT for Real Time Applica...IJERA Editor
Digital watermarking is an essential technique to add hidden copyright notices or secret messages to digital audio, image, or image forms. In this paper we introduce a new approach for digital image watermarking for real time applications. We have successfully implemented the digital watermarking technique on digital images based on 2-level Discrete Wavelet Transform and compared the performance of the proposed method with Level-1 and Level-2 and Level-3 Discrete Wavelet Transform using the parameter peak signal to noise ratio. To make the watermark robust and to preserve visual significant information a 2-Level Discrete wavelet transform used as transformation domain for both secret image and original image. The watermark is embedded in the original image using Alpha blending technique and implemented using Matlab Simulink.
Comparative Study on Watermarking & Image Encryption for Secure CommunicationIJTET Journal
Over the past decades, research in security has concentrated on the development of algorithms and protocols for authentication, encryption and integrity of data. Despite tremendous advances, several security problems still afflict system’s. In this android app watermarking and encryption is being applied on images and data. Because of the human visual system’s low sensitivity to small changes and the high flexibility of digital media, anyone can easily make small changes in digital data with low perceptibility. Here watermarking and encryption are being performed in wavelet domain. Here in watermarking, the coefficients of watermarks are being embedded with the coefficients of the original image. Encryption is being done in wavelet domain so that the probability of an intruder trying to access the contents is very much minimized. Thus, this model provides a high level of security.
Digital watermarking has been proposed as a solution to the problem of copyright protection of
multimedia documents in networked environments. There are two important issues that watermarking
algorithms need to address. First, watermarking schemes are required to provide trustworthy evidence for
protecting rightful ownership. Second, good watermarking schemes should satisfy the requirement of
robustness and resist distortions due to common image manipulations (such as filtering, compression,
etc.). In this paper, a watermarking algorithm is proposed based on the Discrete Wavelet Transform
(DWT), Fractional Fourier Transform (FrFT) and Singular value decomposition (SVD). Analysis and
experimental results show that the proposed watermarking method performs well in both security and
robustness.
Quality - Security Uncompromised and Plausible Watermarking for Patent Infrin...CSCJournals
The most quoted applications for digital watermarking is in the context of copyright-protection of digital (multi-)media. In this paper we offer a new digital watermarking technique, which pledges both Security and Quality for the image for the Patent protection. This methodology uses tale techniques like Shuffling, Composition & Decomposition, and Encryption & Decryption to record the information of a protected primary image and the allied watermarks. The quadtree can aid the processing of watermark and AES provides added security to information. Besides that, we intend a novel architecture for Patent Protection that holds promise for a better compromise between practicality and security for emerging digital rights management application. Security solutions must seize a suspicious version of the application-dependent restrictions and competing objectives.
Digital watermarking knowledge is a leading edge research field and it mainly focuses on the
intellectual property rights, hides data and embedded inside an image to show authenticity or proof
of ownership, discovery and authentication of the digital media to protect the important documents.
Digital watermarking can help to verify ownership, to recognize a misappropriate person and find the
marked documents. One of the significant technological actions of the last two decades was the
attack of digital media in a complete range of everyday life aspects.
Digital data can be stored efficiently with a very high quality and it can be manipulated very
easily using computers. In addition digital data can be transmitted in a fast and inexpensive way
through data communication networks without losing quality. According to the necessary study of
digital image watermarking, the digital watermarking model consists of two modules, which are
watermark embedding module and watermark extraction and detection module.
Report on Digital Watermarking Technology vijay rastogi
Digital watermarking is the process of embedding information into digital multimedia content such that the information (which we call the watermark) can later be extracted or detected for a variety of purposes including copy prevention and control.
Abstract: The increasing amount of applications using digital multimedia technologies has accentuated the need to provide copyright protection to multimedia data. This paper reviews one of the data hiding techniques - digital image watermarking. Through this paper we will explore some basic concepts of digital image watermarking techniques.Two different methods of digital image watermarking namely spatial domain watermarking and transform domain watermarking are briefly discussed in this paper. Furthermore, two different algorithms for a digital image watermarking have also been discussed. Also the comparision between the different algorithms,tests performed for the robustness and the applications of the digital image watermarking have also been discussed.
A Survey on Video Watermarking Technologies based on Copyright Protection and...Editor IJCATR
Digital Watermark is class of marker or symbol secretly embedded in a multimedia signal such as Audio, Image or Video. It
is used to identify the ownership of the multimedia signal. Video watermarking is an emerging area for various applications like copy
control broadcast monitoring, video authentication, copyright protection and enhanced video coding. The main objective of this paper
is to present survey and comparisons of various available techniques on video watermarking based on copyright protection and
identification. Comparative study of various technologies gives the significant information about the PSNR, payload, quality factor
and also the various attacks used in video watermarking techniques. The best techniques in various scenarios are discussed in this
paper which will help the research scholars in field of video watermarking.
STAGE STAFFING SCHEME FOR COPYRIGHT PROTECTION IN MULTIMEDIAIJNSA Journal
Copyright protection has become a need in today’s world. To achieve a secure copyright protection we embedded some information in images and videos and that image or video is called copyright protected. The embedded information can’t be detected by human eye but some attacks and operations can tamper that information to breach protection. So in order to find a secure technique of copyright protection, we have analyzed image processing techniques i.e. Spatial Domain (Least Significant Bit (LSB)), Transform Domain (Discrete Cosine Transform (DCT)), Discrete Wavelet Transform (DWT) and there are numerous algorithm for watermarking using them. After having a good understanding of the same we have proposed a novel algorithm named as Stage Staffing Algorithm that generates results with high effectiveness, additionally we can use self extracted-watermark technique to increase the security and automate the process of watermark image. The proposed algorithm provides protection in three stages. We have implemented the algorithm and results of the simulations are shown. The various factors affecting spatial domain watermarking are also discussed.
BLIND EXTRACTION OF DIGITAL WATERMARKING ALGORITHM FOR COLOR IMAGESijma
Digital watermark technology hides copyright information in digital images, effectively protecting the
copyright of digital images. At present, the color image digital watermarking algorithm still has defects
such as the inability to balance robustness, invisibility and the weak anti-attack ability. Aiming at the
above problems, this paper studies the digital watermarking method based on discrete wavelet transform
and discrete cosine transform. Then this paper proposes a color image blind digital watermarking
algorithm based on QR code. First, convert the color image from RGB space to YCbCr space, extract the Y
component and perform the second-level discrete wavelet transform. secondly, block the LL2 subband and
perform the discrete cosine transform. finally, use the embedding method to convert the watermark
information after the Arnold transform embedded in the block. The experimental results show that the
PSNR of the color image embedded with the QR code is 56.7159 without being attacked. After being
attacked, its PSNR and NC values are respectively 30dB and 0.95 or more, which proves that the algorithm
has good robustness and can achieve watermarking blind extraction.
BLIND EXTRACTION OF DIGITAL WATERMARKING ALGORITHM FOR COLOR IMAGESijma
Digital watermark technology hides copyright information in digital images, effectively protecting the
copyright of digital images. At present, the color image digital watermarking algorithm still has defects
such as the inability to balance robustness, invisibility and the weak anti-attack ability. Aiming at the
above problems, this paper studies the digital watermarking method based on discrete wavelet transform
and discrete cosine transform. Then this paper proposes a color image blind digital watermarking
algorithm based on QR code. First, convert the color image from RGB space to YCbCr space, extract the Y
component and perform the second-level discrete wavelet transform. secondly, block the LL2 subband and
perform the discrete cosine transform. finally, use the embedding method to convert the watermark
information after the Arnold transform embedded in the block. The experimental results show that the
PSNR of the color image embedded with the QR code is 56.7159 without being attacked. After being
attacked, its PSNR and NC values are respectively 30dB and 0.95 or more, which proves that the algorithm
has good robustness and can achieve watermarking blind extraction.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
B011110614
1. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 11, Issue 1, Ver. I (Jan. - Feb .2016), PP 06-14
www.iosrjournals.org
DOI: 10.9790/2834-11110614 www.iosrjournals.org 6 | Page
A Hybrid Model of Watermarking Scheme for Color Image
Authentication Using Discrete Wavelet Transform and Singular
Value Decomposition
Sukanta Kumar Tulo, Dr. Nalinikanta Barpanda, Subhrajit Pradhan,
A. Amiya Kumar Gupta
Department of Electronics Engineering, GIET, GUNUPUR, INDIA
Abstract: Digital Watermarking is a process of embedding information in the multimedia content (host or
cover image) for image authentication. An ideal watermarking system would embed an amount of information
that could not be removed or altered without making the cover object entirely unusable. Over the past few years
digital watermarking has become popular due to its significance in content authentication and legal ownership
for digital multimedia data. A digital watermark is a sequence of information containing the owner’s copyright.
It is inserted invisibly in another image so that it can be extracted at later times for the evidence of rightful
ownership. Available digital watermarking techniques can be categorized into one of the two domains, viz.,
spatial and transform, according to the embedding domain of the host image. Based on these domains digital
watermarking can be done by FFT, DCT, DWT, SVD. The analysis proves that the proposed DWT-SVD hybrid
model is much more superior to other models as it is found to be more robust and effective. The results revealed
that the hybrid model is able to withstand a variety of attacks and shows high level of security.
Keywords: Digital Watermarking, Discrete Wavelet Transform, Hybrid model, Singular Value Decomposition,
Peak Signal to Noise Ratio (PSNR).
I. Introduction
The growth of digital media and the fact that unlimited numbers of perfect copies of such media can be
illegally produced is a threat to the rights of content owners. A copy of digital media is an exact duplicate of the
original. The authors of a work are hesitant to make such information available on the Internet as it may be
copied and retransmitted without the permission of the author. An issue facing electronic commerce on the
Internet for digital information is how to protect the copyright and intellectual property rights of those who
legally own or posses’ digital works. Copyright protection involves ownership authentication and can be used to
identify illegal copies. One approach to copyrighting is to mark works by adding information about their
relationship to the owner by a digital watermark. Digital watermarking is the process of embedding information
into a digital signal which may be used to verify its authenticity or the identity of its owners, in the same manner
as paper bearing a watermark for visible identification. In digital watermarking, the signal may be audio,
pictures, or video. This information may be perceptible or imperceptible to the human senses. Early
watermarking work investigated how documents can be marked so they can be traced in the photocopy process.
If the signal is copied, then the information also is carried in the copy. A signal may carry several different
watermarks at the same time. In visible digital watermarking, the information is visible in the picture or video.
Typically, the information is text or a logo, which identifies the owner of the media. The image on the right has
a visible watermark. When a television broadcaster adds its logo to the corner of transmitted video, this also is a
visible watermark. In invisible digital watermarking, information is added as digital data to audio, picture, or
video, but it cannot be perceived as such (although it may be possible to detect that some amount of information
is hidden in the signal). The watermark may be intended for widespread use and thus, is made easy to retrieve
or, it may be a form of Steganography, where a party communicates a secret message embedded in the digital
signal. Digital watermarks are employed in an attempt to provide proof of ownership and identify illicit copying
and distribution of multimedia information. This contributes an overview of information hiding methods for
digital media and proposes a new way of watermark technique. The main objective of this work is to develop a
watermarking technique to satisfy both imperceptibility and robustness requirements. To achieve this objective
different watermarking scheme like DWT and SVD are discussed and a hybrid model of watermarking scheme
based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed. In our
approach, the watermark is embedded on the elements of singular values of the cover image’s DWT sub bands.
Remaining paper is organized as follows: section 2 discusses the existing related work in the field of digital
image watermarking. Section 3 explains the proposed watermarking model. Section 4 shows the result and
performance analysis. Section 5 contains conclusion.
2. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 7 | Page
II. Related Work
2.1 Literature Review
G. Bhatnagar et.al [1] represented a reference watermarking scheme based on DWT-SVD for an image.
Here a basic idea has been given regarding this scheme. J. Sang et.al. [2] Investigated the fragility and
robustness of binary-phase only filter-based fragile/semi fragile digital image watermarking. Here main concern
is given on fragile and semi fragile digital watermarking and the robustness is been calculated. X.W Kong et.al
[7], proposed the scheme for Object Watermarks for Digital Images and Video. He proposed the SVD based
scheme for embedding the watermarks in the digital image and coloured video. Z. Xinzhong et.al. [10], has
developed A modern Digital Watermarking Algorithm Based on Improved SVD. The improved algorithm is
applied on different samples of images and verified that the improved algorithm is more robust than the
algorithm based on SVD.
2.2 Different Schemes of Watermarking
General digital watermark life-cycle phases with embedding-, attacking and detection and retrieval
functions. The information to be embedded in a signal is called a digital watermark, although in some contexts
the phrase digital watermark means the difference between the watermarked signal and the cover signal. The
signal where the watermark is to be embedded is called the host signal. A watermarking system is usually
divided into three distinct steps, embedding, attack, and detection. In embedding, an algorithm accepts the host
and the data to be embedded, and produces a watermarked signal. Then the watermarked digital signal is
transmitted or stored, usually transmitted to another person. If this person makes a modification, this is called an
attack. There are many possible modifications, for example, lossy compression of the data (in which resolution
is diminished), cropping an image or video or intentionally adding noise. Detection (often called extraction) is
an algorithm which is applied to the attacked signal to attempt to extract the watermark from it. If the signal was
unmodified during transmission, then the watermark still is present and it may be extracted. In robust digital
watermarking applications, the extraction algorithm should be able to produce the watermark correctly, even if
the modifications were strong. In fragile digital watermarking, the extraction algorithm should fail if any change
is made to the signal.
Figure 1: Digital Watermarking Life Cycle
2.2.1 Watermarking Using DWT
Discrete wavelet transform (DWT) is a transform-domain technique where the watermark is embedded
by modulating the magnitude of coefficients in a transform domain, such as wavelet transform. Due to its
excellent spatial-frequency localization properties, the DWT is very suitable to identify areas in the cover image
where a watermark can be imperceptibly embedded. The main idea behind DWT results from multiresolution
analysis, which involves decomposition of an image in frequency channels of constant bandwidth on a
logarithmic scale. It has advantages such as similarity of data structure with respect to the resolution and
available decomposition at any level. The DWT can be implemented as a multistage transformation. An image
is decomposed into four sub bands denoted LL, LH, HL, and HH at level 1 in the DWT domain, where LH, HL
and HH represent the finest scale wavelet coefficients and LL stands for the coarse-level coefficients. The LL
sub band can further be decomposed to obtain another level of decomposition. The decomposition process
continues on the LL sub band until the desired number of levels determined by the application is reached. Since
human eyes are much more sensitive to the low-frequency part (the LL sub band), the watermark can be
embedded in the other three sub bands to maintain better image quality.
2.2.2 Watermarking Using SVD
Singular value decomposition (SVD) is a transform-domain technique where the watermark is
embedded by modulating the magnitude of coefficients in a transform domain. One of attractive mathematical
properties of SVD is that slight variations of singular values do not affect the visual perception of the cover
3. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 8 | Page
image, which motivates the watermark embedding procedure to achieve better transparency and robustness.
From the perspective of image processing, an image can be viewed as a matrix with nonnegative scalar entries.
The SVD of an image A with size m×m is given by A = USV T
, where U and V are orthogonal matrices, and S =
diag(λi) is a diagonal matrix of singular values λi, i = 1, . . . , m, which are arranged in decreasing order. The
columns of U are the left singular vectors, whereas the columns of V are the right singular vectors of image A.
The basic idea behind the SVD-based watermarking techniques is to find the SVD of the cover image or each
block of the cover image, and then modify the singular values to embed the watermark.
III. Proposed Hybrid Model Of Watermarking Using Dwt & Svd
In this approach, the watermark is not embedded directly on the wavelet coefficients but rather than on
the elements of singular values of the cover image’s DWT sub bands. Since performing SVD on an image is
computationally expensive, this study aims to develop a hybrid DWT-SVD based watermarking scheme that
requires less computation effort to yield better performance. After decomposing the cover image into four sub
bands by one-level DWT, we apply SVD only to the intermediate frequency sub bands and embed the
watermark into the singular values of the afore mentioned sub bands to meet the imperceptibility and robustness
requirements.
The main properties of this approach can be identified as:
It needs less SVD computation than other methods
Unlike most existing DWT-SVD-based algorithms, which embed singular values of the
watermark into the singular values of the cover image, our approach directly embeds the
watermark into the singular values of the cover image to better preserve the visual perceptions
of images.
The DWT-SVD watermarking scheme can be formulated as given here.
a) Watermark embedding:
1) Use one-level Haar DWT to decompose the cover image A into four sub bands (i.e., LL, LH, HL, and HH).
2) Apply SVD to LH and HL sub bands, i.e.
Ak
= Uk
Sk
V kT
, k= 1, 2 (1)
Where k represents one of two sub bands.
3) Divide the watermark into two parts:
W = W1
+W2
...Where Wk
denotes half of the watermark.
4) Modify the singular values in HL and LH sub bands with half of the watermark image and then apply SVD to
them, respectively, i.e.,
Sk
+ αWk
= (2)
Where α denotes the scale factor. The scale factor is used to Control the strength of the watermark to be
inserted.
5) Obtain the two sets of modified DWT coefficients, i.e.
A∗k
= Uk
V kT
, k= 1, 2 (3)
6) Obtain the watermarked image by performing the inverse DWT using two sets of modified DWT coefficients
and two sets of non modified DWT coefficients.
The block diagram representation of the above mentioned procedure of watermark embedding is shown
in figure 2.
4. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 9 | Page
Figure 2: Watermark embedding
b) Watermark extraction:
1) Use one-level Haar DWT to decompose the watermarked (possibly distorted) image A∗W into four sub
bands: LL, LH, HL, and HH.
2) Apply SVD to the LH and HL sub bands, i.e.
= U∗k
V ∗kT
, k= 1, 2 (4)
Where k represents one of two sub bands.
3) Compute D∗k
= , k = 1, 2.
4) Extract half of the watermark image from each sub band, i.e.,
W∗k
= (D∗k
− Sk
)/α, k = 1, 2 (5)
5) Combine the results of Step 4 to obtain the embedded watermark:
W∗ = W∗1
+W∗2
.
The block diagram representation of the above mentioned procedure of watermark extraction is shown
in figure 3.
Figure 3: Watermark Extraction
c) Sequence Followed
The approach mainly dealt with the following items in sequence
1. Representing an image in the form of a Matrix
2. Taking out the Transformation let it be DWT or SVD
3. Embedding the watermark/secret image with the cover image to get the watermarked image
4. Neglecting fine details which also involves in elimination of noise
5. Reconstructing the watermark image from the watermarked image.
6. Calculating the PSNR for various levels of approximations and comparing them.
Transformation and Reconstruction
DWT performs wavelet decomposition of vector X with respect to a particular wavelet or particular
wavelet filters that you specify. Instead of transmitting the original matrix as a whole, proper choice of these
coefficients is made out and only selected coefficients are transmitted. The reverse procedure is carried out
5. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 10 | Page
while reconstructing the image. The inverse transformation is carried out for each of the available coefficients
and the representation matrix is obtained. IDWT carries out Wavelet reconstruction.
PSNR (Peak signal to noise ratio)
As a measure of the quality of a watermarked image, the peak signal-to noise ratio (PSNR) was used.
We use the PSNR as an objective means of performance. PSNR is used to measure the difference between two
images. It is defined as
PSNR=20* Log10 (b/rms)
Where b is the largest possible value of the signal (typically 255 or 1), and rms is the root mean
square difference between two images. The PSNR is given in decibel units (dB), which measure the ratio of the
peak signal and the difference between two images. An increase of 20 dB corresponds to a ten-fold decrease in
the rms difference between two images. There are many versions of signal to noise ratios, but the PSNR is very
common in image processing, probably because it gives better sounding numbers than other measures.
IV. Result And Performance Analysis
4.1 Result Using DWT Scheme of Watermarking
The cover image and the watermark image to be watermarked are shown in the figure 4 and figure 5
respectively.
Figure 4: Original Cover Image Figure 5: Watermark Image
The watermarked image obtained from the DWT scheme is shown in figure 6.
Figure 6: Watermarked Image Using DWT
Figure 7 and Figure 8 represents the difference between the original cover image and the watermarked
image and key generated respectively.
6. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 11 | Page
Figure 7: Difference Image Figure 8: Key Generated
The calculated PSNR values in DWT scheme with different scaling factor (α) are listed in Table 1.
Table 1: PSNR values for different scaling factor in DWT scheme
4.2 Result Using SVD Scheme of Watermarking
Figure 9 and figure 10 shows the watermarked image and watermarked with noise image after SVD
technique respectively.
Figure 9: Watermarked Image Figure 10: Watermarked and Noised Image
The watermark image can be reconstructed from the watermarked image and the recovered
watermark image is shown in the figure 11.
Figure 11: Recovered Watermark Image
Figure 12, 13, 14 and 15 shows the watermarking of a text file in cover image using SVD scheme of
watermarking.
α = 0.01 α = 0.05 α = 0.09
40.1538 38.8375 37.0752
7. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 12 | Page
Figure 12: Cover image Figure 13: Watermark to be embedded
Figure 14: Watermarked image Figure 15: Watermarked and noised image
The watermark text can be reconstructed from the watermarked image. The recovered watermark
image is shown in the figure 16.
Figure 16: Recovered watermark image
The calculated PSNR values in SVD scheme with different scaling factor (α) are listed in Table 2.
Table 2: PSNR values for different scaling factor in SVD scheme
4.3 Result using the hybrid DWT-SVD Scheme of Watermarking
The figures 17 and 18 show the cover image and the gray scale converted image of the cover image
used in DWT-SVD scheme of watermarking
α = 0.01 α = 0.05 α = 0.09
40.2439 38.9437 37.0012
8. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 13 | Page
Figure 17: Cover image Figure 18: Gray scale converted image
The figures 19 and 20 show the watermark image and the gray scale converted image of the watermark
image.
Figure 19: Cover image Figure 20: Gray scale converted image
The figures 21 and 22 show the SVD image of the cover image and watermarked image after applying
DWT-SVD technique.
Figure 21: SVD image Figure 22: Watermarked image
The calculated PSNR values in DWT-SVD scheme with different scaling factor (α) are listed in the
Table 3.
Table 3: PSNR values for different scaling factor in DWT-SVD scheme
Here three watermarking schemes namely: Watermarking using DWT, SVD and a hybrid model using
DWT & SVD are implemented and compared. Watermark extraction was performed on watermarked images
using these three models. The output images and results are observed to compare the performance of these
α = 0.01 α = 0.05 α = 0.09
40.4387 39.0513 37.1996
9. A Hybrid Model of Watermarking Scheme for Color Image Authentication Using
DOI: 10.9790/2834-11110614 www.iosrjournals.org 14 | Page
schemes. The values of the scaling factors are taken as 0.01, 0.05 and 0.09 and the results are illustrated in Table
4.
WATERMARKING
SCHEME
PSNR,
WITH α =0.01
PSNR,
WITH α =0.05
PSNR,
WITH α =0.09
DWT 40.1538 38.8375 37.0752
SVD 40.2439 38.9437 37.0012
DWT-SVD 40.4387 39.0513 37.1996
Table 4: Comparison of PSNR for DWT, SVD and Hybrid model DWT-SVD Scheme of Watermarking
V. Conclusion
Hybrid image watermarking technique based on DWT and SVD has been presented, where the
watermark is embedded on the singular values of the cover image’s DWT sub bands. The technique fully
exploits the respective feature of these two transform domain methods: Spatio-frequency localization of DWT
and SVD efficiently represents intrinsic algebraic properties of an image. The results show that the proposed
hybrid DWT-SVD scheme has both the significant improvement in imperceptibility and the robustness. It is
observed that the larger the scaling factor, the stronger is the robustness of the applied watermarking scheme
and it can withstand a variety of image-processing attacks. In addition to quantitative measurement, the hybrid
model has also given better visual perceptions of the extracted watermarks. Thus the DWT-SVD hybrid model
watermarking scheme significantly outperforms the other two schemes of watermarking.
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