Locally optimum image watermark detector based on statistical modeling of SWT-EFMs magnitudes

2022 ◽  
Vol 65 ◽  
pp. 103105
Author(s):  
Xiang-yang Wang ◽  
Xin Shen ◽  
Jia-lin Tian ◽  
Pan-pan Niu ◽  
Hong-ying Yang
Keyword(s):  
Statistical Modeling ◽  
Image Watermark

scholarly journals A New Statistical Image Watermark Detector in RHFMs Domain using Beta Exponential Distribution

2021 ◽  
Author(s):  
Panpan Niu ◽  
Jing Tian ◽  
Jialin Tian ◽  
Xiangyang Wang
Keyword(s):  
Exponential Distribution ◽  
Statistical Modeling ◽  
Decision Rules ◽  
Exponential Model ◽  
Distribution Model ◽  
Statistical Distributions ◽  
Robust Modeling ◽  
Image Watermark ◽  
Alternative Approaches ◽  
Blind Image

Abstract The detection of watermarks can be achieved by statistical approaches. How to select robust modeling object, appropriate statistical model, and decision rules is one of the major issues in statistical image watermark detection. In this paper, we propose a new image watermark detector in robust fast radial harmonic Fourier moments (FRHFMs) magnitudes domain, wherein the Beta exponential distribution model and locally most powerful (LMP) decision rule are used. We first investigate the statistical modeling of the robust FRHFMs magnitudes by the Beta exponential distribution. It is shown that the Beta exponential distribution model fits the empirical data more accurately than the formerly employed statistical distributions, such as the Cauchy, Weibull, BKF and Exponential, do. Motivated by the statistical modeling results, we design a blind image watermark detector in FRHFMs magnitudes domain by using Beta exponential distribution and LMP test. Also, we utilize the Beta-exponential model to derive the closed-form expressions for the watermark detector. We provide comparative experimental results to alternative approaches to demonstrate the advantages of the proposed image watermark detector.

Statistical modeling of drill pipes operational life-time under a regular loading

2020 ◽  
pp. 30-33
Author(s):  
V.I. Kucheryavy ◽  
◽  
A.M. Sharygin ◽  
V.L. Savich ◽  
S.N. Milkov ◽  
...  
Keyword(s):  
Statistical Modeling ◽  
Life Time ◽  
Operational Life ◽  
Drill Pipes

EVALUATION OF THE RELIABILITY OF COMPLEX TECHNICAL RECONFIGURATION SYSTEMS BY STATISTICAL MODELING METHOD

2019 ◽  
pp. 84-88
Author(s):  
A.Yu. Kulakov
Keyword(s):  
Normal Distribution ◽  
Statistical Modeling ◽  
Quantitative Estimate ◽  
Failure Time ◽  
Modeling Method ◽  
System Failure ◽  
Similar System ◽  
Orbit Control ◽  
Reliability Characteristics ◽  
Complex Technical System

Goal. Assess the reliability of a complex technical system with periodic reconfiguration and compare the results obtained a similar system, but without reconfiguration. Materials and methods. In this article uses the method of statistical modeling (Monte Carlo) to assess the reliability of complex system. We using the normal and exponential distribution of failure time for modeling failures of system elements. Reconfiguration algorithm is the algorithm proposed for the attitude and orbit control system of spacecraft. Results. A computer program has been developed for assessing reliability on the basis of a statistical modeling method, which makes it possible to evaluate systems of varying complexity with exponential and normal distribution, as well as with and without periodic reconfiguration. A quantitative estimate of the reliability as a function of the probability of system failure is obtained. Conclusion. It has been demonstrated that a system with reconfiguration has the best reliability characteristics, both in the case of exponential and normal distribution of failures.

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