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Comparative performance of multiwavelet-based image watermaking schemes

WSEAS Transactions on systems 2006年第5期5卷 1041-1047页

作者： Kumsawat, Prayoth Attakitmongcol, Kitti Srikaew, Arthit Signal and Image Processing Research Group School of Electrical Engineering Suranaree University of Technology 111 University Avenue Nakhon Ratchasima 30000 Thailand Intelligent System Research Group School of Electrical Engineering Suranaree University of Technology 111 University Avenue Nakhon Ratchasima 30000 Thailand

This paper presents the performance comparisons of the two image watermarking schemes in the multiwavelet transform domain. The first one is based on the concept of the watermarking technique that has been designed in the previous chapter and the second one is based on the code division multiple access (CDMA) technique. The embedding information is a visually recognizable pattern which can be extractable not just detectable to characterize the owner. Both techniques do not require the original image in the watermark extraction process. The normalized correlation and bit error rate are used to evaluate the robustness of the watermark and the evaluation process of robustness is performed on the watermarked images from both techniques under the same image quality. The attacks include JPEG compression, JPEG2000 compression, lowpass filtering and a series of selected attacks from StirMark benchmark.

关键词： Imaging systems

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(Semi-)Analytic Gaussian Mixture Filter

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IFAC Proceedings Volumes 2011年第1期44卷 10014-10020页

作者： Marco F. Huber Frederik Beutler Uwe D. Hanebeck Variable Image Acquisition and Processing Research Group Fraunhofer Institute of Optronics System Technologies and Image Exploitation (IOSB) Karlsruhe Germany Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

Abstract In nonlinear filtering, special types of Gaussian mixture filters are a straightforward extension of Gaussian filters, where linearizing the system model is performed individually for each Gaussian component. In this paper, two novel types of linearization are combined with Gaussian mixture filters. The first linearization is called analytic stochastic linearization, where the linearization is performed analytically and exactly, i.e., without Taylor-series expansion or approximate sample-based density representation. In cases where a full analytical linearization is not possible, the second approach decomposes the nonlinear system into a set of nonlinear subsystems that are conditionally integrable in closed form. These approaches are more accurate than fully applying classical linearization.

关键词： State Estimation Nonlinear systems Stochastic systems Decomposition Methods

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Reconfiguration of the brain during aesthetic experience on Chinese calligraphy—Using brain complex networks

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Visual Informatics 2022年第1期6卷 35-46页

作者： Rui Li Xiaofei Jia Changle Zhou Junsong Zhang National Engineering Laboratory for Educational Big Data Central China Normal UniversityWuhanHubeiChina Mind Art&Computation GroupDepartment of Artificial IntelligenceSchool of InformaticsXiamen UniversityChina Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and TourismChina Center for the Study of Brain and Language Qufu Normal UniversityRizhaoChina Faculty of Education The Edmond J.Safra Brain Research Center for the Study of Learning DisabilitiesUniversity of HaifaHaifaIsrael

Chinese calligraphy,as a well-known performing art form,occupies an important role in the intangible cultural heritage of *** studies focused on the psychophysiological benefits of Chinese *** attention has been paid to its aesthetic attributes and effectiveness on the cognitive *** complement our understanding of Chinese calligraphy,this study investigated the aesthetic experience of Chinese cursive-style calligraphy using brain functional network *** stayed on the coach and rested for several ***,they were requested to appreciate artwork of cursive-style *** showed that(1)changes in functional connectivity between frontooccipital,fronto-parietal,bilateral parietal,and central–occipital areas are prominent for calligraphy condition,(2)brain functional network showed an increased normalized cluster coefficient for calligraphy condition in alpha2 and gamma *** results demonstrate that the brain functional network undergoes a dynamic reconfiguration during the aesthetic experience of Chinese *** evidence that the aesthetic experience of Chinese calligraphy has several similarities with western art while retaining its unique characters as an eastern traditional art form.

关键词： Chinese calligraphy Aesthetic experience Electroencephalogram Brain functional connectivity Complex network

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The effects of transformation methods in image watermarking

The effects of transformation methods in image watermarking

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IEEE Region 10 International Conference TENCON

作者： P. Kumsawat K. Attakitmongcol A. Srikaew Signal and Image Processing Research Group School of Electrical Engineering Institute of Engineering Suranaree University슠of Technology Nakhon Ratchasima Thailand Intelligent System Research Group School of Electrical Engineering Institute of Engineering Suranaree University슠of Technology Nakhon Ratchasima Thailand

Image watermarking provides copyright protection and becomes very crucial for ownership verification of digital images. In this paper, we investigate the effects of different types of transformations in image watermarking algorithm including discrete cosine transform, discrete wavelet transform, and discrete multiwavelet transform. We also provide a brief overview of the multiwavelet transform since it is relatively new as compared to the other transforms. The efficiencies of these transforms are discussed by evaluating watermarked image quality and robustness of the watermark. Experimental results show that the multiwavelet transform method is superior to other two methods in term of image quality.

关键词： Watermarking Discrete wavelet transforms Discrete transforms Discrete cosine transforms Robustness Spread spectrum communication Digital images Image quality Frequency Image processing

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AN AUTOFOCUS NETWORK FOR MULTI-CHANNEL PHASE ERRORS WITH APPLICATION TO TOMOSAR IMAGING

AN AUTOFOCUS NETWORK FOR MULTI-CHANNEL PHASE ERRORS WITH APP...

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IET International Radar Conference 2023, IRC 2023

作者： Wang, Muhan Gao, Silin Zhang, Zhe Qiu, Xiaolan Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781839539954

Synthetic aperture radar (SAR) tomography (TomoSAR) has garnered significant attention due to its capability for three-dimensional reconstruction. Compressed sensing (CS) methods are widely employed to address the TomoSAR inversion challenge. Nevertheless, practical applications reveal phase errors among different channels, resulting in defocusing and blurring when relying solely on CS for 3D reconstruction. Current state-of-the-art autofocus techniques suffer from prohibitive computational complexity, limiting their applicability to large-scale 3D imaging. In pursuit of efficient TomoSAR 3-D autofocusing, we proposed ASAMP-Net, an innovative deep unfolding network. Operating within a two-step framework, each layer comprises two stages: phase error estimation and iterative scattering coefficient reconstruction using the sparse adaptive matching pursuit (SAMP) algorithm. Additionally, phase error estimation is obtained through mathematical derivation, while challenges associated with fixed sparsity and limited efficiency in conventional methods are mitigated through deep learning techniques. Simulation experiments and real data validation affirm the effectiveness and superiority of the proposed method. © The Institution of Engineering & Technology 2023.

关键词： Radar imaging

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GRIDLESS DOA ESTIMATION FOR AUTOMOTIVE RADARS WITH VARIOUS ARRAY GEOMETRIES: THE NON-VANDERMONDE ATOMIC SOFT THRESHOLDING APPROACH

GRIDLESS DOA ESTIMATION FOR AUTOMOTIVE RADARS WITH VARIOUS A...

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IET International Radar Conference 2023, IRC 2023

作者： Gao, Silin Wang, Muhan Zhang, Zhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China

ISBN: (纸本)9781839539954

This paper is centered on gridless direction of arrival (DoA) estimation for single-snapshot data collected by non-uniform linear arrays (NLAs) in the context of automotive applications. While recent single-snapshot DoA estimation algorithms rooted in grid-based compressed sensing (CS) offer super-resolution capabilities, they are notably sensitive to discrepancies between the assumed sparsity basis and the actual basis. Furthermore, the existing atomic soft thresholding (AST) algorithm, a promising gridless sparse recovery technique within the Toeplitz model, is constrained to uniform linear arrays (ULAs) exhibiting Vandermonde structure in their array manifolds. However, in automotive scenarios, it becomes imperative to efficiently apply gridless DoA estimation to NLAs featuring non-Vandermonde array manifolds. In this paper, we introduce the non-Vandermonde atomic soft thresholding (NVAST) algorithm and employ it for DoA estimation in NLAs. The novel algorithm establishes a link between Vandermonde and non-Vandermonde atoms by decomposing non-Vandermonde vectors and addressing them using semi-definite programming (SDP). Simulation and measurement experiments conducted with automotive radars underscore the remarkable performance of our proposed method. © The Institution of Engineering & Technology 2023.

关键词： Automotive radar

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GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC NORM MINIMIZATION WITH EFFICIENCY

GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC...

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2022 International Conference on Radar systems, RADAR 2022

作者： Gao, Silin Zhang, Zhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China

ISBN: (纸本)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) enables the reconstruction and three-dimensional (3D) localization of targets based on multiple two-dimensional (2D) observations of the same scene. The resolving along the elevation direction can be treated as a line spectrum estimation problem. However, traditional super-resolution spectrum estimation algorithms require multiple snapshots and uncorrelated targets. Meanwhile, as the most popular TomoSAR imaging method in modern years, compressed sensing (CS) based methods suffer from the gridding mismatch effect which markedly degrades the imaging performance. As a gridless CS approach, atomic norm minimization can avoid the gridding effect but requires enormous computing resources. Addressing the above issues, this paper proposes an improved fast ANM algorithm to TomoSAR elevation focusing by introducing the IVDST-ANM algorithm, which reduces the huge computational complexity of the conventional time-consuming semi-positive definite programming (SDP) by the iterative Vandermonde decomposition and shrinkage-thresholding (IVDST) approach, and retains the benefits of ANM in terms of gridless imaging and single snapshot recovery. We conducted experiments using simulated data to evaluate the performance of the proposed method, and reconstruction results of an urban area from the SARMV3D-Imaging 1.0 dataset are also presented. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Compressed sensing

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Contrastive Learning for Robust Android Malware Familial Classification

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IEEE Transactions on Dependable and Secure Computing 2022年 1-14页

作者： Wu, Yueming Dou, Shihan Zou, Deqing Yang, Wei Qiang, Weizhong Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China University of Texas at Dallas Dallas USA National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Due to its open-source nature, Android operating system has been the main target of attackers to exploit. Malware creators always perform different code obfuscations on their apps to hide malicious activities. Features extracted from these obfuscated samples through program analysis contain many useless and disguised features, which leads to many false negatives. To address the issue, in this paper, we demonstrate that obfuscation-resilient malware family analysis can be achieved through contrastive learning. The key insight behind our analysis is that contrastive learning can be used to reduce the difference introduced by obfuscation while amplifying the difference between malware and other types of malware. Based on the proposed analysis, we design a system that can achieve robust and interpretable classification of Android malware. To achieve robust classification, we perform contrastive learning on malware samples to learn an encoder that can automatically extract robust features from malware samples. To achieve interpretable classification, we transform the function call graph of a sample into an image by centrality analysis. Then the corresponding heatmaps can be obtained by visualization techniques. These heatmaps can help users understand why the malware is classified as this family. We implement IFDroid and perform extensive evaluations on two datasets. Experimental results show that IFDroid is superior to state-of-the-art Android malware familial classification systems. Moreover, IFDroid is capable of maintaining a 98.4% F1 on classifying 69,421 obfuscated malware samples. IEEE

关键词： Semantics

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DYNAMICAL BEHAVIOR OF A STOCHASTIC HBV INFECTION MODEL WITH LOGISTIC HEPATOCYTE GROWTH

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Acta Mathematica Scientia 2017年第4期37卷 927-940页

作者：刘群蒋达清史宁中 Tasawar HAYAT Ahmed ALSAEDI School of Mathematics and Statistics Key Laboratory of Applied Statistics of MOENortheast Normal UniversityChangchun 130024China School of Mathematics and Statistics Guangxi Universities Key Lab of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulinGuangxi 537000China Nonlinear Analysis and Applied Mathematics(NAAM)Research Group Department of MathematicsFaculty of ScienceKing Abdulaziz UniversityJeddah 121589Saudi Arabia College of Science China University of Petroleum(East China)Qingdao 266580China Department of Mathematics Quaid-i-Azam University 45320Islamabad 44000Pakistan

This paper is concerned with a stochastic HBV infection model with logistic growth. First, by constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of ergodic stationary distribution of the solution to the HBV infection model. Then we obtain sufficient conditions for extinction of the disease. The stationary distribution shows that the disease can become persistent in vivo.

关键词： stochastic HBV infection model extinction stationary distribution Lyapunov function

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The Influence of Ceramic Coating on Fatigue Crack Growth Behaviour of X17CrNi15-2 Stainless Steel

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Engineering（科研） 2020年第2期12卷 140-149页

作者： Ran Li Wenshu Wei Shoubin Li Rui Zhao Hao Liu Jiankai Zhang Jian Ye Huigang Wu Yao Xu Fei Xiao Mengyu Wu Dalong Wang Jingbin Chen Wei Wang Na Gao Rongming Chen Intelligent Control Technology Branch China Coal Research Institute Beijing China Big-Data Research Branch China Coal Research Institute Beijing China Beijing Tiandi-Marco Electro-Hydraulic Control System Company Ltd. China Coal Technology and Engineering Group Beijing China.

Fatigue crack growth tests were carried out on the SEN B3 precracked specimens, with dimensions in accordance with ISO 12108 requirements. The specimens were made of martensitic stainless steel, X17CrNi15-2, and some of them were modified by the ceramic coating deposition surface treatment. The effects of ceramic coating, on the fatigue crack growth behaviour of hollow shaft specimens, were experimentally investigated. Fatigue crack growth rates, da/dN, were characterised, using the power law relationship between da/dN (in mm/cycle) and the stress intensity factor range, ΔK (in MPa∙m0.5). The two constants of the correlation are 7.9768 × 10−9 and 2.8107 for the parent material, and those for the coated material are 2.4391 × 10−9 and 3.1990, respectively. Microstructural analyses were carried out on the tested specimens, which shows that the maximum hardness of the ceramic coating is higher than that of substrate by a factor of ~3.2. The dimple fracture dominates the final fracture mechanism for the parent material, and the combination of fatigue, ductile fracture and cleavage dominates the final fracture mechanism for the coated material, based on the SEM analyses. EDS tests’ results reveal that the parent material specimen shows higher levels of C at matrix regions along with Fe- and O-rich regions, compared with the coated material specimen.

关键词： Fatigue Crack Growth SEN B3 Precracked Specimen X17CrNi15-2 Ceramic Coating Deposition Surface Treatment Corrosion Resistance

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