Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

Two-dimensional C_(2)N-based single-atom catalyst with complex microenvironment for enhanced electrochemical nitrogen reduction:A descriptor-based design

The catalytic descriptor with operational feasibility is highly desired towards rational design of high-performance catalyst especially the electrode/electrolyte solution interface working under mild conditions.Herein,we demonstrate that the descriptorΩparameterized by readily accessible intrinsic properties of metal center and coordination is highly operational and efficient in rational design of single-atom catalyst(SAC)for driving electrochemical nitrogen reduction(NRR).Using twodimensional metal(M)-B_(x)P_(y)S_(z)N_m@C_(2)N as prototype SAC models,we reveal that^(*)N_(2)+(H~++e~-)→^(*)N_(2)H acts predominantly as the potential-limiting step(PLS)of NRR on M-B_(2)P_(2)S_(2)@C_(2)N and M-B_(1)P_(1)S_(1)N_(3)@C_(2)N regardless of the distinction in coordination microenvironment.Among the 28 screened M active sites,withΩvalues close to the optimal 4,M-B_(2)P_(2)S_(2)@C_(2)N(M=V(Ω=3.53),Mo(Ω=5.12),and W(Ω=3.92))and M-B_(1)P_(1)S_(1)N_(3)@C_(2)N(M=V(Ω=3.00),Mo(Ω=4.34),and W(Ω=3.32))yield the lowered limiting potential(U_(L))as-0.45,-0.54.-0.36,-0.58,-0.25,and-0.24 V,respectively,thus making them the promising NRR catalysts.More importantly,these SACs are located around the top of volcano-shape plot of U_(L) versusΩ,re-validatingΩas an effective descriptor for accurately predicting the high-activity NRR SACs even with complex coordination.Our study unravels the relationship between active-site structure and NRR performance via the descriptorΩ,which can be applied to other important sustainable electrocatalytic reactions involving activation of small molecules viaσ-donation andπ^(*)-backdonation mechanism.

Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.

W-系统矩和Fourier变换下Volume Descriptors不变特征的三维模型检索

针对V-系统矩难以构造快速算法的不足,提出一种W-系统矩及其快速算法,并融合volume descriptors不变特征应用于三维模型检索.首先对模型体素化;其次计算体素模型的W-系统矩和物体运动不变量,得到特征向量;最后进行特征融合及匹配.实验结果表明,该算法的检索效率和性能均优于三维球面调和函数方法和三维Legendre矩方法.

Static Output Feedback H_∞ Controllers Design for Descriptor Linear Systems Based on LMI

This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of a static output feedback H ∞ controller are given in terms of LMIs. Furthermore, the design method of H ∞ controllers is provided using the solutions to the LMIs.

基于改进的Orientation_based Minutia Descriptor指纹检索算法

指纹检索通过有效地缩小指纹匹配空间,在很大程度上提高了指纹识别的效率,成为自动指纹识别系统中一个非常重要的研究方向。主要做了两方面的工作:发现已有Orientation_based Minutia Descriptor(OMD)存在旋转相关的问题并通过改进OMD相似度计算方法有效地解决了该问题;提出了一种基于改进的OMD指纹检索算法,其主要过程为:依据改进的OMD相似度计算方法计算当前输入指纹与库中指纹每两个细节点间的OMD相似度,并基于该相似度获取粗糙对应点集;对粗糙对应点集中的每对对应点对,通过构造相邻局部特征向量进一步验证其正确性,获取精炼对应点集;重复上述两步骤获取当前输入指纹与库中剩余指纹的精炼对应点集;统计当前输入指纹与库中所有指纹的精炼对应点集中对应点数量,提取数量最多的前N个精炼对应点集,返回其在指纹库中对应的指纹标识。实验验证了提出算法的有效性。

Extract the Output Signal Characteristics of DC-DC Converter Based on Fourier Descriptor

The precondition of realizing feedback controlling DC DC converter to avoid chaotic state is to judge the behavior of the converter and take corresponding measures. In this paper, the output signals under different circuit parameters of the PWM buck converter have been analyzed. The method of using Fourier descriptor to extract output signals characteristics is put forward and proved to be a gist of identifying and classifying the behavior of DC DC converter. This method can establish a good foundation fo...

Shape retrieval using multi-level included angle functions-based Fourier descriptor

An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation translation and scaling are the intrinsic properties of the MIAFs.For each contour point the multi-level included angles are obtained based on the paired line segments derived from unequal-arc-length partitions of contour.And a Fourier descriptor derived from multi-level included angle functions MIAFD is presented for efficient shape retrieval.The proposed descriptor is evaluated with the standard performance evaluation method on three shape image databases the MPEG-7 database the Kimia-99 database and the Swedish leaf database. The experimental results of shape retrieval indicate that the MIAFD outperforms the existing Fourier descriptors and has low computational complexity.And the comparison of the MIAFD with other shape description methods also shows that the proposed descriptor has the highest precision at the same recall value which verifies its effectiveness.

Attitude sensor fault diagnosis based on Kalman filter of discrete-time descriptor system

To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to esti-mate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.

Delay-dependent H-infinity control for linear descriptor systems with delay in state

A deky-dependent H-infinity control for descriptor systems with a state-delayis investigated. The purpose of the problem is to design a linear memoryless state-feedbackcontroller such that the resulting closed-loop system is regular, impulse free and stable with anH-infinity norm bound. Firstly, a deky-dependent bounded real lemma(BRL) of the time-deky descriptorsystems is presented in terms of linear matrix inequalities(LMIs) by using a descriptor modeltransformation of the system and by taking a new Lyapunov-Krasovsii functional. The introducedfunctional does not require bounding for cross terms, so it has less conservation. Secondly, withthe help of the obtained bounded real lemma, a sufficient condition for the existence of a newdeky-dependent H-infinity state-feedback controller is shown in terms of nonlinear matrixinequalities and the solvability of the problem can be obtained by using an iterative algorithminvolving convex optimization. Finally, numerical examples are given to demonstrate theeffectiveness of the new method presented.

Robust H-infinity fault-tolerant control for uncertain descriptor systems by dynamical compensators

The problem of robust H-infinity fault-tolerant control against sensor failures for a class of uncertain descriptor systems via dynamical compensators is considered. Based on H-infinity theory in descriptor systems, a sufficient condition for the existence of dynamical compensators with H-infinity fault-tolerant function is derived and expressions for the gain matrices in the compensators are presented. The dynamical compensator guarantees that the resultant colsed-loop system is admissible; furthermore, it maintains certain H-infinity norm performance in the normal condition as well as in the event of sensor failures and parameter uncertainties. A numerical example shows the effect of the proposed method.

An Angle Structure Descriptor for Image Retrieval

This paper presents an efficient image feature representation method, namely angle structure descriptor(ASD), which is built based on the angle structures of images. According to the diversity in directions, angle structures are defined in local blocks. Combining color information in HSV color space, we use angle structures to detect images. The internal correlations between neighboring pixels in angle structures are explored to form a feature vector. With angle structures as bridges, ASD extracts image features by integrating multiple information as a whole, such as color, texture, shape and spatial layout information. In addition, the proposed algorithm is efficient for image retrieval without any clustering implementation or model training. Experimental results demonstrate that ASD outperforms the other related algorithms.

Decentralized robust H-infinity descriptor output feedback control for value-bounded uncertain descriptor large-scale systems

For a class of value-bounded uncertain descriptor large-scale interconnected systems, the decentralized robust H∞ descriptor output feedback control problem is investigated. A design method based on the bounded real lemma is developed for a decentralized descriptor dynamic output feedback controller, which is reduced to a feasibility problem for a nonlinear matrix inequality （NLMI）. It is proposed to solve the NLMI iteratively by the idea of homotopy, where some of the variables are fixed alternately at each iteration to reduce the NLMI to a linear matrix inequality （LMI）. A given example shows the efficiency of this method .

Eigenstructure Assignment in a Class of Second-order Descriptor Linear Systems: A Complete Parametric Approach

In this paper eigenstructure assignment via proportional-plus-derivative feedback is investigated for a class of second-order descriptor linear systems. Under certain conditions, simple, general and complete parametric solutions of both finite closed-loop eigenvector matrices and feedback gain matrices are derived. The parametric approach utilizes directly original system data, involves manipulations only on n-dimensional matrices, and reveals all the design degrees of freedom which can be further utilized to achieve certain additional system specifications. A numerical example shows the effect of the proposed approach.

Non-fragile observer-based passive control for descriptor systems with time-delay

This paper investigates the problem of non-fragile observer-based passive control for descriptor systems with time-delay. The perturbations in both the control gain and observer gain of the observer-based controller are considered. For the cases of the additive perturbations and multiplicative perturbations, sufficient conditions are given such that the closed-loop systems are admissible and passive with dissipation η. The observer-based controller gains could be obtained from the solutions of linear matrix inequalities （LMIs）. Moreover, the maximum dissipation of the system is provided. Simulation examples are given to show the effectiveness of the deign methods.

Passivity Control for Uncertain T-S Fuzzy Descriptor Systems

By means of matrix decomposition method a criterion is presented for the admissibility of T-S fuzzy descriptor system. Then, the problem of passivity control is studied for a kind of T-S fuzzy descriptor system with uncertain parameters, and sufficient conditions which make the closed-loop system admissible and strictly passive are obtained based on linear matrix inequality (LMI). The nonstrict LMIs restricted conditions which characterize the descriptor system are transformed into strict ones, so testing admissibility and passivity of the system can be finished simultaneously. The design scheme of state feedback controller is also obtained. Finally, a numerical example is given to show the validity and feasibility of the proposed approach.

Observers for Descriptor Systems with Slope-restricted Nonlinearities

This paper addresses the observer design problem for a class of nonlinear descriptor systems whose nonlinear terms are slope-restricted. The full-order observer is formulated as a nonlinear descriptor system. A linear matrix inequality （LMI） condition is derived to construct the full-order observer. The existence and uniqueness of the solution to the obtained observer system are guaranteed. Furthermore, under the same LMI condition and a common assumption, a reduced-order observer is designed. Finally, the design methods are reduced to a strict LMI problem and illustrated by a numerical example.

Shape Descriptor with Morphology Method for Color-based Tracking

Tracking images using shape descriptor can be more accurate than using other existing methods and it is most useful when the environment is complex. However the existing methods with shape descriptor get more labeled parts to compare and detect the object in an image, which makes the computation more complicated. Thus, we need a trade-off between the accuracy and efficiency requirements. This paper aims to bridge this gap between the accuracy and efficiency requirements by using morphology method. To improve the original monochromatic object detecting system, we propose a new color descriptor to preprocess the image with polychromatic object. Experiments have been conducted and shown the proposed method has made a great improvement in the time complexity minimization comparing with the performances of the original detection algorithm.

Robust H_∞ control for uncertain descriptor systems with state and control delay

The problem of robust stabilization for uncertain continuous descriptor system with state and control delay is considered. The time-varying parametric uncertainty is assumed to be norm-bounded. The purpose of the robust stabilization is to design a memoryless state feedback law such that the resulting closed-loop system is robustly stable A sufficient condition that uncertain continuous descriptor system is robustly stabilizabled by state feedback law is derived in terms of linear matrix inequality （LMI）. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Generalized regularity and regularizability of rectangular descriptor systems

The notion of generalized regularity is proposed for rectangular descriptor systems. Generalized regularizability of a rectangular descriptor system via different feedback forms is considered. Necessary and sufficient conditions for generalized regularizability are obtained, which are only dependent upon the open-loop coefficient matrices. It is also shown that under these necessary and sufficient conditions, all the generalized regularizing feedback controllers form a Zarisky open set. A numerical example demonstrates the proposed results.