Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

Obstacle Avoidance and Multitarget Tracking of a Super Redundant Modular Manipulator Based on Bezier Curve and Particle Swarm Optimization

A super redundant serpentine manipulator has slender structure and multiple degrees of freedom.It can travel through narrow spaces and move in complex spaces.This manipulator is composed of many modules that can form different lengths of robot arms for different application sites.The increase in degrees of freedom causes the inverse kinematics of redundant manipulator to be typical and immensely increases the calculation load in the joint space.This paper presents an integrated optimization method to solve the path planning for obstacle avoidance and discrete trajectory tracking of a super redundant manipulator.In this integrated optimization,path planning is established on a Bezier curve,and particle swarm optimization is adopted to adjust the control points of the Bezier curve with the kinematic constraints of manipulator.A feasible obstacle avoidance path is obtained along with a discrete trajectory tracking by using a follow-the-leader strategy.The relative distance between each two discrete path points is limited to reduce the fitting error of the connecting rigid links to the smooth curve.Simulation results show that this integrated optimization method can rapidly search for the appropriate trajectory to guide the manipulator in obtaining the target while achieving obstacle avoidance and meeting joint constraints.The proposed algorithm is suitable for 3D space obstacle avoidance and multitarget path tracking.

Graphics Evolutionary Computations in Higher Order Parametric Bezier Curves

This work demonstrates in practical terms the evolutionary concepts and computational applications of Parametric Curves.Specific cases were drawn from higher order parametric Bezier curves of degrees 2 and above.Bezier curves find real life applications in diverse areas of Engineering and Computer Science,such as computer graphics,robotics,animations,virtual reality,among others.Some of the evolutionary issues explored in this work are in the areas of parametric equations derivations,proof of related theorems,first and second order calculus related computations,among others.A Practical case is demonstrated using a graphical design,physical hand sketching,and programmatic implementation of two opposite-faced handless cups,all evolved using quadratic Bezier curves.The actual drawing was realized using web graphics canvas programming based on HTML 5 and JavaScript.This work will no doubt find relevance in computational researches in the areas of graphics,web programming,automated theorem proofs,robotic motions,among others.

A transition method based on Bezier curve for trajectory planning in cartesian space

In order to smooth the trajectory of a robot and reduce dwell time,a transition curve is introduced between two adjacent curves in three-dimensional space.G2 continuity is guaranteed to transit smoothly.To minimize the amount of calculation,cubic and quartic Bezier curves are both analyzed.Furthermore,the contour curve is characterized by a transition parameter which defines the distance to the corner of the deviation.How to define the transition points for different curves is presented.A general move command interface is defined for receiving the curve limitations and transition parameters.Then,how to calculate the control points of the cubic and quartic Bezier curves is analyzed and given.Different situations are discussed separately,including transition between two lines,transition between a line and a circle,and transition between two circles.Finally,the experiments are carried out on a six degree of freedom(DOF) industrial robot to validate the proposed method.Results of single transition and multiple transitions are presented.The trajectories in the joint space are also analyzed.The results indicate that the method achieves G2 continuity within the transition constraint and has good efficiency and adaptability.

Shape Control and Modification of Rational Bezier Curve and Surface

A Bezier interpolation approach is proposed which uses local generation of endpoint slopes and forces the curve and the surface to pass through an arbitrarily specified point to control and modify the shape of curve and surface, making the result satisfactory.

VERIFYING THE IMPLICITIZATION FOR MULAE FORDEGREE n RATIONAL BEZIER CURVES

This is a continuation of short communication([1]). In [1] a verification of the implicitization equation for degree two rational Bezier curves is presented which does not require the use of resultants. This paper presents these verifications in the general cases, i.e., for degree n rational Bezier curves. Thus some interesting interplay between the structure of the n x n implicitization matrix and the de Casteljau algorithm is revealed.

Degree elevation from Bzier curve to C-Bzier curve with corner cutting form

The existing results of curve degree elevation mainly focus on the degree of algebraic polynomials. The paper considers the elevation of degree of the trigonometric polynomial, from a Bezier curve on the algebraic polynomial space, to a C-Bezier curve on the algebraic and trigonometric polynomial space. The matrix of degree elevation is obtained by an operator presentation and a derivation pyramid. It possesses not a recursive presentation but a direct expression. The degree elevation process can also be represented as a corner cutting form.

Judging or setting weight steady-state of rational Bézier curves and surfaces

Many works have investigated the problem of reparameterizing rational B^zier curves or surfaces via MSbius transformation to adjust their parametric distribution as well as weights, such that the maximal ratio of weights becomes smallerthat some algebraic and computational properties of the curves or surfaces can be improved in a way. However, it is an indication of veracity and optimization of the reparameterization to do prior to judge whether the maximal ratio of weights reaches minimum, and verify the new weights after MSbius transfor- mation. What＇s more the users of computer aided design softwares may require some guidelines for designing rational B6zier curves or surfaces with the smallest ratio of weights. In this paper we present the necessary and sufficient conditions that the maximal ratio of weights of the curves or surfaces reaches minimum and also describe it by using weights succinctly and straightway. The weights being satisfied these conditions are called being in the stable state. Applying such conditions, any giving rational B6zier curve or surface can automatically be adjusted to come into the stable state by CAD system, that is, the curve or surface possesses its optimal para- metric distribution. Finally, we give some numerical examples for demonstrating our results in important applications of judging the stable state of weights of the curves or surfaces and designing rational B6zier surfaces with compact derivative bounds.

Direction monotonicity for a rational Bézier curve

The monotonicity of a rational Bezier curve, usually related to an explicit function, is determined by the used coordinate system. However, the shape of the curve is independent of the coordinate system. To meet the affine invariant property, a kind of generalized mono- tonicity, called direction monotonicity, is introduced for rational Bezier curves. The direction monotonicity is applied to both planar and space curves and to both Cartesian and affine co- ordinate systems, and it includes the traditional monotonicity as a subcase. By means of it, proper affine coordinate systems may be chosen to make some rational Bezier curves monotonic. Direction monotonic interpolation may be realized for some of the traditionally nonmonotonic data as well.

Algorithms and Identities for(q, h)-Bernstein Polynomials and(q, h)-Bézier Curves–A Non-Blossoming Approach

We establish several fundamental identities, including recurrence relations, degree elevation formulas, partition of unity and Marsden identity, for quantum Bernstein bases and quantum Bezier curves. We also develop two term recurrence relations for quantum Bernstein bases and recursive evaluation algorithms for quantum Bezier curves. Our proofs use standard mathematical induction and other elementary techniques.

Re-parameterization of Bézier Curves by Square Approximation with Endpoint Constraints

In order to get an approximation with better effect of pararneterization of Bezier curves, we proposed a method for arc-length parameterization and the corresponding algorithms by square approximation for the discrete even de-parameterization of the curves. This method is simple and easy to implement, and the property of the approximation has no change compared with the original curve. A quantitative criterion for estimating the effect of parameterization is also built to quantitatively characterize the parameterization effect of the algorithms. As a result, the nearly arc-length parameterized curve has a smaller relative deviation using either the algorithm with point constraint at endpoints or the algorithm with point constraint plus the first derivative constraint at endpoints. Experiments show that after re-parameterization with our algorithms, the relative deviation will have at least a 20% reduction.

APPROXIMATE MERGING OF BE ZIER CURVES

In this paper, a simple method for merging of Bezier curves is presented by using constrained optimization method. The use of the “discrete” coefficient norm in L2 sense greatly simplifies the merging process. Furthermore, continuity at the endpoint of curves are considered in the merging process.

A Real-time Look-ahead Trajectory Planning Methodology for Multi Small Line Segments Path

When a robot is required to machine a complex curved workpiece with high precision and speed,the tool path is typically dispersed into a series of points and transmitted to the robot.The conventional trajectory planning method requires frequent starts and stops at each dispersed point to complete the task.This method not only reduces precision but also causes damage to the motors and robot.A real-time look-ahead algorithm is proposed in this paper to improve precision and minimize damage.The proposed algorithm includes a path-smoothing algorithm,a trajectory planning method,and a bidirectional scanning module.The path-smoothing method inserts a quintic Bezier curve between small adjacent line segments to achieve G^(2)continuity at the junctions.The trajectory planning method utilizes a quartic polynomial and a double-quartic polynomial that can achieve a constant velocity at the velocity limitation.The bidirectional scanning module calculates the velocity at each trajectory planning segment point,simplifying calculation complexity and can be run in real time.The feasibility of the proposed algorithm is verified through simulations and experiments,which can be run in real time.In addition,high machining precision can be achieved by adjusting the relevant parameters.

Research on AGV task path planning based on improved A^(*) algorithm

Background Automatic guided vehicles(AGVs)have developed rapidly in recent years and have been used in several fields,including intelligent transportation,cargo assembly,military testing,and others.A key issue in these applications is path planning.Global path planning results based on known environmental information are used as the ideal path for AGVs combined with local path planning to achieve safe and rapid arrival at the destination.Using the global planning method,the ideal path should meet the requirements of as few turns as possible,a short planning time,and continuous path curvature.Methods We propose a global path-planning method based on an improved A^(*)algorithm.The robustness of the algorithm was verified by simulation experiments in typical multiobstacle and indoor scenarios.To improve the efficiency of the path-finding time,we increase the heuristic information weight of the target location and avoid invalid cost calculations of the obstacle areas in the dynamic programming process.Subsequently,the optimality of the number of turns in the path is ensured based on the turning node backtracking optimization method.Because the final global path needs to satisfy the AGV kinematic constraints and curvature continuity condition,we adopt a curve smoothing scheme and select the optimal result that meets the constraints.Conclusions Simulation results show that the improved algorithm proposed in this study outperforms the traditional method and can help AGVs improve the efficiency of task execution by planning a path with low complexity and smoothness.Additionally,this scheme provides a new solution for global path planning of unmanned vehicles.

Approximate Degree Reduction of Bezier Curves

Degree reduction of parametric curves and surfaces is an important process in data communication between CAD systems. The degenerate condition of Bezier curves and the constrained optimization method are used to develop a new degree reduction method for Bezier curves. An error analysis of the degree reduction is also given. The degree reduction scheme is combined with a subdivision algorithm to generate lower degree approximations which are within some preset error tolerance of the prescribed Bezier curve. Geometric continuity between adjacent curve segments is also considered in the subdivision/degree reduction process.

Energy Expenditure of Trotting Gait Under Different Gait Parameters

Robots driven by batteries are clean, quiet, and can work indoors or in space. However, the battery endurance is a great problem. A new gait parameter design energy saving strategy to extend the working hours of the quadruped robot is proposed. A dynamic model of the robot is established to estimate and analyze the energy expenditures during trotting. Given a trotting speed, opti- mal stride frequency and stride length can minimize the energy expenditure. However, the relationship between the speed and the optimal gait parameters is nonlinear, which is difficult for practical application. Therefore, a simplified gait parameter design method for energy saving is pro- posed. A critical trotting speed of the quadruped robot is found and can be used to decide the gait parameters. When the robot is travelling lower than this speed, it is better to keep a constant stride length and change the cycle period. When the robot is travelling higher than this speed, it is better to keep a constant cycle period and change the stride length. Simulations and experiments on the quadruped robot show that by using the proposed gait parameter design approach, the energy expenditure can be reduced by about 54% compared with the 100 mm stride length under 500 mm/s speed. In general, an energy expenditure model based on the gait parameter of the quadruped robot is built and the trotting gait parameters design approach for energy saving is proposed.

Multi-objective Trajectory Planning Method based on the Improved Elitist Non-dominated Sorting Genetic Algorithm

Robot manipulators perform a point-point task under kinematic and dynamic constraints.Due to multi-degreeof-freedom coupling characteristics,it is difficult to find a better desired trajectory.In this paper,a multi-objective trajectory planning approach based on an improved elitist non-dominated sorting genetic algorithm(INSGA-II)is proposed.Trajectory function is planned with a new composite polynomial that by combining of quintic polynomials with cubic Bezier curves.Then,an INSGA-II,by introducing three genetic operators:ranking group selection(RGS),direction-based crossover(DBX)and adaptive precision-controllable mutation(APCM),is developed to optimize travelling time and torque fluctuation.Inverted generational distance,hypervolume and optimizer overhead are selected to evaluate the convergence,diversity and computational effort of algorithms.The optimal solution is determined via fuzzy comprehensive evaluation to obtain the optimal trajectory.Taking a serial-parallel hybrid manipulator as instance,the velocity and acceleration profiles obtained using this composite polynomial are compared with those obtained using a quintic B-spline method.The effectiveness and practicability of the proposed method are verified by simulation results.This research proposes a trajectory optimization method which can offer a better solution with efficiency and stability for a point-to-point task of robot manipulators.

A Real-time Cutting Model Based on Finite Element and Order Reduction

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in real-time.Therefore,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time performance.The proposed model uses the finite element model to construct a deformation model of the virtual lung.Meanwhile,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation computation.In addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual lung.Then,the Bezier curve is adopted to draw the incision outline after the virtual lung has been cut.Finally,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual lung.Experimental results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

A Hybrid Path Planning Method Based on Articulated Vehicle Model

Due to the unique steering mechanism and driving characteristics of the articulated vehicle,a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle.First,Support Vector Machine(SVM)theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin,and then,several key points are selected from the optimal zero potential curves by using Longest Accessible Path(LAP)method.Next,the Cubic Bezier(CB)curve is adopted to connect the curve that satisfies the curvature constraint of the articulated vehicle between every two key points.Finally,Back and Forth Rapidly-exploring Random Tree with Course Correction(BFRRT-CC)is designed to connect paths that do not meet articulated vehicle curvature requirements.Simulation results show that the proposed hybrid path planning method can search a feasible path with a 90-degree turn,which meets the demand for obstacle avoidance and articulated vehicle back-and-forth movement.

Generating routes for autonomous driving in vehicle-to-infrastructure communications

The study of vehicular networks has attracted considerable interest in academia and the industry.In the broad area,connected vehicles and autonomous driving are technologies based on wireless data communication between vehicles or between vehicles and infrastructures.A Vehicle-to-Infrastructure(V2I)system consists of communications and computing over vehicles and related infrastructures.In such a system,wireless sensors are installed in some selected points along roads or driving areas.In autonomous driving,it is crucial for a vehicle to figure out the ideal routes by the communications between its equipped sensors and infrastructures then the vehicle is automatically moving along the routes.In this paper,we propose a Bezier curve based recursive algorithm,which effectively creates routes for vehicles through the communication between the On-Board Unit(OBU)and the Road-Side Units(RSUs).In addition,this approach generates a very low overhead.We conduct simulations to test the proposed algorithm in various situations.The experiment results demonstrate that our algorithm creates almost ideal routes.