scholarly journals Imperceptible–Visible Watermarking to Information Security Tasks in Color Imaging

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2374
Author(s):  
Oswaldo Ulises Juarez-Sandoval ◽  
Francisco Javier Garcia-Ugalde ◽  
Manuel Cedillo-Hernandez ◽  
Jazmin Ramirez-Hernandez ◽  
Leobardo Hernandez-Gonzalez
Keyword(s):  
Real World ◽  
Copyright Protection ◽  
Color Image ◽  
Image Watermarking ◽  
Additional Information ◽  
Visible Watermarking ◽  
Real World Applications ◽  
Digital Reproduction ◽  
Two Stages

Digital image watermarking algorithms have been designed for intellectual property, copyright protection, medical data management, and other related fields; furthermore, in real-world applications such as official documents, banknotes, etc., they are used to deliver additional information about the documents’ authenticity. In this context, the imperceptible–visible watermarking (IVW) algorithm has been designed as a digital reproduction of the real-world watermarks. This paper presents a new improved IVW algorithm for copyright protection that can deliver additional information to the image content. The proposed algorithm is divided into two stages: in the embedding stage, a human visual system-based strategy is used to embed an owner logotype or a 2D quick response (QR) code as a watermark into a color image, maintaining a high watermark imperceptibility and low image-quality degradation. In the exhibition, a new histogram binarization function approach is introduced to exhibit any watermark with enough quality to be recognized or decoded by any application, which is focused on reading QR codes. The experimental results show that the proposed algorithm can embed one or more watermark patterns, maintaining the high imperceptibility and visual quality of the embedded and the exhibited watermark. The performance evaluation shows that the method overcomes several drawbacks reported in previous algorithms, including geometric and image processing attacks such as JPEG and JPEG2000.

An intelligent and blind dual color image watermarking for authentication and copyright protection

2020 ◽  
Author(s):  
Sajjad Bagheri Baba Ahmadi ◽  
Gongxuan Zhang ◽  
Mahdi Rabbani ◽  
Lynda Boukela ◽  
Hamed Jelodar
Keyword(s):  
Copyright Protection ◽  
Color Image ◽  
Image Watermarking ◽  
Color Image Watermarking ◽  
Dual Color

A New Robust Color Image Watermarking Based on DWT and DRT

2013 ◽  
Vol 278-280 ◽  
pp. 1366-1373 ◽  
Author(s):  
Zi Teng ◽  
Xiu Feng Qiu ◽  
Jian Wei Liu
Keyword(s):  
Digital Watermarking ◽  
Copyright Protection ◽  
Color Image ◽  
Image Watermarking ◽  
Discrete Wavelet ◽  
Color Image Watermarking ◽  
Ridgelet Transform ◽  
Color Image Watermark ◽  
Robust Image ◽  
Watermarking Scheme

The copyright protection of multimedia information is more and more important in the digital age, digital watermarking is a solution to address the topic. This paper proposes a new robust image watermarking scheme based on discrete ridgelet transform (DRT) and discrete wavelet transform (DWT). The scheme respectively embeds a copy of color image watermark into DWT domain and DRT domain, and uses a conception of semi-watermark. Experiment results demonstrate that the watermark can resist various attacks such as adding Gaussian or Union Distribution Noise, JPEG compression, brightness adjustment, contrast adjustment, altering color balance, lens blur, zooming in or out, cropping and some combined attacks etc.

scholarly journals Unsupervised Quality Estimation for Neural Machine Translation

2020 ◽  
Vol 8 ◽  
pp. 539-555
Author(s):  
Marina Fomicheva ◽  
Shuo Sun ◽  
Lisa Yankovskaya ◽  
Frédéric Blain ◽  
Francisco Guzmán ◽  
...  
Keyword(s):  
Machine Translation ◽  
Real World ◽  
State Of The Art ◽  
Black Box ◽  
Test Time ◽  
Quality Estimation ◽  
Neural Machine Translation ◽  
Real World Applications ◽  
Unsupervised Approach

Quality Estimation (QE) is an important component in making Machine Translation (MT) useful in real-world applications, as it is aimed to inform the user on the quality of the MT output at test time. Existing approaches require large amounts of expert annotated data, computation, and time for training. As an alternative, we devise an unsupervised approach to QE where no training or access to additional resources besides the MT system itself is required. Different from most of the current work that treats the MT system as a black box, we explore useful information that can be extracted from the MT system as a by-product of translation. By utilizing methods for uncertainty quantification, we achieve very good correlation with human judgments of quality, rivaling state-of-the-art supervised QE models. To evaluate our approach we collect the first dataset that enables work on both black-box and glass-box approaches to QE.

What Is the Quality of Quality of Medical Care Measures?: Rashomon -like Relativism and Real-World Applications

2003 ◽  
Vol 46 (1) ◽  
pp. 5-20 ◽  
Author(s):  
Marshall H. Chin ◽  
Naoko Muramatsu
Keyword(s):  
Medical Care ◽  
Real World ◽  
Real World Applications ◽  
Quality Of Medical Care

scholarly journals Mining gold from implicit models to improve likelihood-free inference

2020 ◽  
Vol 117 (10) ◽  
pp. 5242-5249 ◽  
Author(s):  
Johann Brehmer ◽  
Gilles Louppe ◽  
Juan Pavez ◽  
Kyle Cranmer
Keyword(s):  
Inverse Problems ◽  
Probability Density ◽  
Real World ◽  
Density Ratio ◽  
Training Data ◽  
Loss Functions ◽  
Additional Information ◽  
Latent Process ◽  
Ratio Estimators

Simulators often provide the best description of real-world phenomena. However, the probability density that they implicitly define is often intractable, leading to challenging inverse problems for inference. Recently, a number of techniques have been introduced in which a surrogate for the intractable density is learned, including normalizing flows and density ratio estimators. We show that additional information that characterizes the latent process can often be extracted from simulators and used to augment the training data for these surrogate models. We introduce several loss functions that leverage these augmented data and demonstrate that these techniques can improve sample efficiency and quality of inference.

scholarly journals Tchebichef image watermarking along the edge using YCoCg-R color space for copyright protection

2019 ◽  
Vol 9 (3) ◽  
pp. 1850 ◽  
Author(s):  
Ferda Ernawan
Keyword(s):  
Copyright Protection ◽  
Image Watermarking ◽  
Color Space ◽  
Digital Image Watermarking ◽  
Tchebichef Moments ◽  
The Matrix ◽  
Edge Based ◽  
Watermarking Scheme ◽  
Matrix Moment

Easy creation and manipulation of digital images present the potential danger of counterfeiting and forgery. Watermarking technique which embeds a watermark into the images can be used to overcome these problems and to provide copyright protection. Digital image watermarking should meet requirements, e.g. maintain image quality, difficult to remove the watermark, quality of watermark extraction, and applicable. This research proposes Tchebichef watermarking along the edge based on YCoCg-R color space. The embedding region is selected by considering the human visual characteristics (HVC) entropy. The selected blocks with minimum of HVC entropy values are transformed by Tchebichef moments. The locations of C(0,1), C(1,0), C(0,2) and C(2,0) of the matrix moment are randomly embedded for each watermark bit. The proposed watermarking scheme produces a good imperceptibility by average SSIM value around 0.98. The watermark recovery has greater resistant after several types of attack than other schemes.

scholarly journals Data Hiding Method for Color AMBTC Compressed Images Using Color Difference

2021 ◽  
Vol 11 (8) ◽  
pp. 3418
Author(s):  
Cheonshik Kim ◽  
Dongkyoo Shin ◽  
Chingnung Yang ◽  
Lu Leng
Keyword(s):  
Data Hiding ◽  
Copyright Protection ◽  
Color Image ◽  
Color Difference ◽  
Adjustment Process ◽  
Absolute Moment ◽  
Compressed Images ◽  
Secret Communication ◽  
Bit Plane

Image compression technology and copyright protection are certainly the important technologies for free exchange of multimedia. For compression of an image, we propose a color Absolute Moment Block Trucation Coding (AMBTC) method using a common bit-plane created by k-means. In addition, a data hiding method based on a color AMBTC using Optimal Pixel Adjustment Process (OPAP) was proposed for copyright protection and confidential secret communication. The number of quantization levels of the proposed color AMBTC is nine per block. Therefore, the edge of the compressed color image can be expressed more delicately. As a result of the simulation, it can be seen that the edge of the image of the color AMBTC is close to the original image. Moreover, the data hiding performance of the proposed method also obtained excellent results. For the experiment, we measured the quality of the image using the Color Difference (CD) we proposed, and the measurement result was very satisfactory.

PatchR

2015 ◽  
Vol 11 (1) ◽  
pp. 30-45
Author(s):  
Magnus Knuth ◽  
Harald Sack
Keyword(s):  
Missing Data ◽  
Real World ◽  
Linked Data ◽  
Real World Applications ◽  
Change Requests ◽  
Incorrect Data ◽  
The Web

Incorrect or outdated data is a common problem when working with Linked Data in real world applications. Linked Data is distributed over the web and under control of various dataset publishers. It is difficult for data publishers to ensure the quality and timeliness of the data all by themselves, though they might receive individual complaints by data users, who identified incorrect or missing data. Indeed, the authors see Linked Data consumers equally responsible for the quality of the datasets they use. PatchR provides a vocabulary to report incorrect data and to propose changes to correct them. Based on the PatchR ontology a framework is suggested that allows users to efficiently report and data publishers to handle change requests for their datasets.

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