Edge Constraints Research Articles

Pulse-coupled neural network and its optimization for segmentation of electrical faults with infrared thermography

This paper describes a method for segmenting electrical equipment fault with infrared thermography by using pulse-coupled neural networks. The pulse coupled neuron model used in PCNN is an optimization of the original neural model, in order to easily control and alter the behavior of neuron activity. In the receptive field, the image and its gradient information are regarded as the inputs of PCNN. The method for adjusting the value of linking coefficient is then derived from the principle of maximum likelihood estimate in the region of temporal pulse outputs, thus building the inner relationship between the parameters and image statistics. Besides, the edge constraint method, which is integrated into the pulse generator, is designed to alter the behavior of the neighboring neurons to be captured. It is shown that the addition of the constraint to the model increases the possibility of desired fault region segmentation. Finally, several experimental results, especially performed on the electrical equipment fault images, show that the proposed model has better performance than some existing PCNN-based models in the performance of image segmentation.

Disparity Refinement in Depth Discontinuity Using Robustly Matched Straight Lines for Digital Surface Model Generation

Dense image matching using remote sensing images is of particular importance for providing ground geometric data for object modeling and analysis. These methods normally operate in a rectified (epipolar) space producing disparity images that are correlated with the final three-dimensional geometry. However, the resulting digital surface models can be problematic on discontinuities of the terrain object, e.g., building edges, which largely limit their practical use for highly accurate object modeling. Existing works put forth efforts for dealing with this issue by defining better edge constraints and more global energy optimization, while intended to improve the disparity maps, it might be challenging to leverage the result of all the pixels through a single energy minimization, leading to either oversmoothed object boundaries or noisy surfaces. In this paper, we propose an intuitive method that integrates straight line primitives to enhance the disparity map. For each matched line, we perform a local discontinuity analysis and propose an intensity-based weighting method for a local plane fitting using iteratively solved weighted least squares adjustment, such that straightness of the object's edges (e.g., buildings) can be preserved, as the straight lines are detected and matched. Experiments on both aerial and satellite dataset show that the proposed method yields visually clear object edges and has achieved higher accuracy (2-3 pixels improvement) around edges than DSM generated from typical stereo matching result (i.e., from semiglobal matching).

A Unified Formulation for Free Vibration of Spherical Cap Based on the Ritz Method

The free vibration characteristic of spherical cap with general edge constraints is studied by means of a unified method. The energy method and Kirchhoff hypothesis are adopted to derive the formulas. The displacement functions are improved based on the domain decomposition method, in which the unified Jacobi polynomials are introduced to represent the displacement function component along circumferential direction. The displacement function component along axial direction is still the Fourier series. In addition, the spring stiffness method forms a unified format to deal with various complex boundary conditions and the continuity conditions at two adjacent segments. Then, the final solutions can be obtained based on the Ritz method. To prove the validity of this method, the results of the same condition are compared with FEM, published literatures, and experiment. The results show that the present method has the advantages of fast convergence, high solution accuracy, simple boundary simulation, etc. In addition, some numerical results of uniform and stepped spherical caps with various geometric parameters and edge conditions are reported.

Multi-Scale Adaptive Level Set Segmentation Method Based on Saliency

Image segmentation is an important research of computer vision. Due to the effects of intensity inhomogeneity, target edge and background complex, it is still challenging to achieve effective segmentation of target adaptively. To solve these issues, an image segmentation method based on saliency and level set is proposed in this paper. First, adaptive initial contour of level set is got by wavelet-based feature probability evaluation (WFPE) model, the initial contour is closer to the target contour, which can reduce background interference and evolve faster. Second, in order to realize the best detection of intensity mutation and locate the target edge more accurately, an edge constraint energy term is introduced with multi-scale information obtained by wavelet transform. Finally, to improve segmentation adaptability and speed, the region information and edge constraint energy term are merged into the adaptive active contour model, the final evolution curve evolves in coarse scale, and then interpolates to get the final segmentation contour. Experimental results show that the proposed method achieves high efficiency in the following aspects: adaptability to images, speed of evolution, close to human visual perception.

Graph Learning Via Edge Constrained Sparse Representation for Image Analysis

The construction of a graph essentially determines the performance of the graph-based image analysis methods. Particularly, the sparse graph is vital in image analysis because of its sparse and adaptive properties for the enormous scale of data. However, most existing graph-based algorithms ignore some valuable natural information, such as edge information of image data. In this paper, we propose a novel graph learning method, called edge constrained sparse representation (ECSR), which makes full use of edge information to refine the similarity among image samples. We believe that it is beneficial to include edge constraints into the construction stage of a graph for image analyses. Compared with conventional graph construction methods, ECSR has not only automatic sparsity and adaptive neighborhood size but also more accurate similarity measurements among natural images. The experimental results on four natural image datasets demonstrate the validity and effectiveness of ECSR for semi-supervised classification and clustering tasks.

Application of First-Order Shear Deformation Theory on Vibration Analysis of Stepped Functionally Graded Paraboloidal Shell with General Edge Constraints.

The paper introduces a semi-analytical approach to analyze free vibration characteristics of stepped functionally graded (FG) paraboloidal shell with general edge conditions. The analytical model is established based on multi-segment partitioning strategy and first-order shear deformation theory. The displacement components along axial direction are represented by Jacobi polynomials, and the Fourier series are utilized to express displacement components in circumferential direction. Based on penalty method about spring stiffness technique, the general edge conditions of doubly curved paraboloidal shell can be easily simulated. The solutions about doubly curved paraboloidal shell were solved by approach of Rayleigh–Ritz. Convergence study about boundary parameters, Jacobi parameters et al. are carried out, respectively. The comparison with published literatures, FEM and experiment results show that the present method has good convergence ability and excellent accuracy.

Three-dimensional dynamic fracture in a transversely isotropic thermoelastic solid: Framework for study

A semi-infinite plane crack is at rest in an unbounded, transversely isotropic, thermoelastic solid. Point forces are applied to the crack faces, and translated with constant, subcritical speed at right angles to the initial crack edge. Fracture occurs, and a dynamic steady state is achieved: The crack edge is no longer rectilinear, but extension and translation speeds are identical. The crack plane contains the axis of material symmetry lies in that plane, and the initial crack edge is not aligned with that axis. An analytical three-dimensional solution is obtained, and a criterion for fracture based on dynamic energy release rate imposed, with kinetic energy included. A nonlinear differential equation for crack edge location and constraint equations result, and together form a framework for study of crack and contact zone geometry.

Modified two-thickness method for measurement of the acoustic properties of porous materials

In this study, a modified two-thickness method to measure acoustic properties of porous materials using surface acoustic impedance is proposed and compared to those obtained by the four-microphone impedance tube and traditional two-thickness methods. In the two-thickness method, the complex propagation constant and characteristic impedance are estimated from the measured surface acoustic impedances, and the sample thicknesses should have a ratio of two. Through the proposed method, the complex characteristic impedance and wavenumber of a porous material are calculated under arbitrary sample thicknesses condition. The surface acoustic impedances for samples of different thicknesses are measured via the two-microphone impedance tube method to estimate their complex acoustic properties. Sensitivity analysis is performed to analyze the measurement uncertainty on the resulting values. The sensitivity depended on the sample thickness and mount edge constraint in the tube. Using the method proposed in this study, acoustic properties are measured accurately with small differences in thickness and surface acoustic impedance.

Implementation of Kriging Surrogate Models for Delamination Detection in Composite Structures

Composite structures are prone to impact and fatigue loads in service which in turn causes defects such as de-lamination. This affects the dynamic characteristics of the composite laminates such as its Natural frequency, Mode shapes and its damping characteristics. Hence it can be used as a prominent indicator for structural health monitoring. This paper focusses on the use of Kriging based surrogate model for the prediction of delamination in Carbon fibre reinforced epoxy composite panels with an edge constraint. The change in natural frequency and mode shapes of the damaged and undamaged model has been taken as the primary damage indicator for the present analysis. The size and location of the damage were predicted from the developed surrogate models. The performance of the proposed approach has been studied experimentally and compared it with numerical simulation and has been found satisfactory. The surrogate approach reduces the computational time considerably without compromising the accuracy.

A new semi-analytical solution method for free vibration analysis of composite rectangular plates with general edge constraints coupled with single piezoelectric layer

In this article, a new approach is presented to study the free vibrations of rectangular composite plates coupled with single piezoelectric layer. The laminated plate with general stacking sequences is subjected to the elastic edge restraints. Based on the first-order shear deformation theory and Hamilton’s principle, the equations of the motion along with boundary conditions of the problem are deduced. To solve the problem, generalized displacements as well as general electric potentials are expanded using the Legendre polynomial series as the base functions. Then, the kinetic and potential energies of the problem are obtained. Afterwards, by means of Lagrange multipliers all the boundary conditions have been added to the energies to form the functional. This energy functional is extremised to get the natural frequencies and mode shapes of the problem through generalized eigenvalue problem. Credibility of the proposed method is verified by comparing the obtained results with those achieved by other theories and finite element method.

Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features

Automatic road extraction from remote-sensing imagery plays an important role in many applications. However, accurate and efficient extraction from very high-resolution (VHR) images remains difficult because of, for example, increased data size and superfluous details, the spatial and spectral diversity of road targets, disturbances (e.g., vehicles, shadows of trees, and buildings), the necessity of finding weak road edges while avoiding noise, and the fast-acquisition requirement of road information for crisis response. To solve these difficulties, a two-stage method combining edge information and region characteristics is presented. In the first stage, convolutions are executed by applying Gabor wavelets in the best scale to detect Gabor features with location and orientation information. The features are then merged into one response map for connection analysis. In the second stage, highly complete, connected Gabor features are used as edge constraints to facilitate stable object segmentation and limit region growing. Finally, segmented objects are evaluated by some fundamental shape features to eliminate nonroad objects. The results indicate the validity and superiority of the proposed method to efficiently extract accurate road targets from VHR remote-sensing images.

A general-threshold filtering method for improving intravoxel incoherent motion parameter estimates

In this study, we present an image denoising method for diffusion-weighted magnetic resonance imaging (DW-MRI) data. Our aim is to improve the estimation of intravoxel incoherent motion (IVIM) parameters using denoised DW-MRI data. A general-threshold filtering (GTF) reconstruction via total variation minimization has been proposed to improve image quality in few-view computed tomography. Here, we applied the combination of GTF and total difference to image denoising. Voxel-wise IVIM analysis was performed using both real and simulated DW-MRI data. Using an institutional review board-approved protocol with written informed consent, DW-MRI imaging was performed at a 3 T hybrid PET/MR system in 10 patients with Hodgkin lymphoma lesions. A simulated phantom consisting of four organs (liver, pancreas, spleen and kidney) was used to generate noisy DW-MRI data according to the IVIM model at different noise levels. DW-MRI data were denoised before IVIM parameter estimation. The proposed image denoising method was compared with the image denoising method using joint rank and edge constraints (JREC). The results of simulated data show that at the lower signal-to-noise ratios the proposed image denoising method outperformed the JREC method in terms of the accuracy and precision of the IVIM parameter estimates. The experimental results also show that the proposed image denoising method could yield better parametric images than the JREC method in terms of noise reduction and edge preservation.

Mesh smoothing of complex geometry using variations of cohort intelligence algorithm

Several approaches including optimization based methods were developed for mesh quality improvement using only node movement, keeping intact the element connectivity. In this research, a socio-inspired optimization approach referred to as cohort intelligence (CI) was investigated for mesh smoothing. Minimization of summation of condition numbers of all elements was the final aim. The geometrical boundaries of the object defined the surface and edge constraints for movement of external nodes. Movement of internal nodes was completely governed by variations of CI algorithm, viz. roulette wheel, follow best, follow better, alienation and random selection, follow worst and follow itself. The approach was demonstrated with pentagonal prism, hexagonal prism and hexagonal prism with hole. The performance of follow best and roulette wheel variations of CI algorithm was observed to be satisfactory as compared to other variations of the algorithm.

Method Based on Edge Constraint and Fast Marching for Road Centerline Extraction from Very High-Resolution Remote Sensing Images

In recent decades, road extraction from very high-resolution (VHR) remote sensing images has become popular and has attracted extensive research efforts. However, the very high spatial resolution, complex urban structure, and contextual background effect of road images complicate the process of road extraction. For example, shadows, vehicles, or other objects may occlude a road located in a developed urban area. To address the problem of occlusion, this study proposes a semiautomatic approach for road extraction from VHR remote sensing images. First, guided image filtering is employed to reduce the negative effects of nonroad pixels while preserving edge smoothness. Then, an edge-constraint-based weighted fusion model is adopted to trace and refine the road centerline. An edge-constraint fast marching method, which sequentially links discrete seed points, is presented to maintain road-point connectivity. Six experiments with eight VHR remote sensing images (spatial resolution of 0.3 m/pixel to 2 m/pixel) are conducted to evaluate the efficiency and robustness of the proposed approach. Compared with state-of-the-art methods, the proposed approach presents superior extraction quality, time consumption, and seed-point requirements.

Tangential Edge Constraint Sensitivity of Nonlinear Stability of CNT-Reinforced Composite Plates under Compressive and Thermomechanical Loadings

AbstractThis paper analytically investigates the buckling and postbuckling of functionally graded composite plates reinforced by single-walled carbon nanotubes (SWCNTs), supported by elastic founda...

Non-Linear Bending of Functionally Graded Thin Plates with Different Moduli in Tension and Compression and Its General Perturbation Solution

In this study, a set of Föppl–von Kármán equations for a bimodular functionally graded thin plate subjected to a uniformly distributed load is established, and its general perturbation solution in axisymmetric case is also obtained under different boundary conditions. First, the equation of equilibrium of the plate is established on the existence of the neutral layer when considering different properties in tension and compression. During the derivation of the consistency equation, the tensile effect in the thin plate with bimodular effect is fully taken into account. The perturbation method is used to solve the set of governing equations under different edge constraints, in which the central deflection and the load of the plate are taken as a perturbation parameter, respectively. The results indicate that the two selections for perturbation parameters are valid and consistent, and the two solutions are convenient for engineering application. This study also shows that the bimodular effect will modify the relation of load versus central deflection of the plate to some extent, and under the same edge constraint, the capacities resisting deformation in different cases of moduli depend on the relative magnitudes among the tensile modulus, the neutral layer modulus, and the compressive modulus.

Object-Based Dense Matching Method for Maintaining Structure Characteristics of Linear Buildings.

In this paper, we proposed a novel object-based dense matching method specially for the high-precision disparity map of building objects in urban areas, which can maintain accurate object structure characteristics. The proposed framework mainly includes three stages. Firstly, an improved edge line extraction method is proposed for the edge segments to fit closely to building outlines. Secondly, a fusion method is proposed for the outlines under the constraint of straight lines, which can maintain the building structural attribute with parallel or vertical edges, which is very useful for the dense matching method. Finally, we proposed an edge constraint and outline compensation (ECAOC) dense matching method to maintain building object structural characteristics in the disparity map. In the proposed method, the improved edge lines are used to optimize matching search scope and matching template window, and the high-precision building outlines are used to compensate the shape feature of building objects. Our method can greatly increase the matching accuracy of building objects in urban areas, especially at building edges. For the outline extraction experiments, our fusion method verifies the superiority and robustness on panchromatic images of different satellites and different resolutions. For the dense matching experiments, our ECOAC method shows great advantages for matching accuracy of building objects in urban areas compared with three other methods.

A weak form quadrature element formulation for geometrically exact thin shell analysis

The present paper addresses a weak form quadrature element formulation for the geometrically exact thin shell model in which the Kirchhoff-Love hypothesis is adopted. The displacement derivative continuity conditions are enforced by the reconstruction of rotation variables at the edges of elements. By the utilization of rotation quaternions, a total Lagrange updating scheme is implemented for edge constraint director rotations. Several numerical examples are presented to illustrate the effectiveness of the proposed formulation and the significant reduction in the number of degrees of freedom in geometrically nonlinear thin shell analysis with large displacements and rotations.

Relief generation from 3D scenes guided by geometric texture richness

Typically, relief generation from an input 3D scene is limited to either bas-relief or high-relief modeling. This paper presents a novel unified scheme for synthesizing reliefs guided by the geometric texture richness of 3D scenes; it can generate both basand high-reliefs. The type of relief and compression coefficient can be specified according to the user’s artistic needs. We use an energy minimization function to obtain the surface reliefs, which contains a geometry preservation term and an edge constraint term. An edge relief measure determined by geometric texture richness and edge z-depth is utilized to achieve a balance between these two terms. During relief generation, the geometry preservation term keeps local surface detail in the original scenes, while the edge constraint term maintains regions of the original models with rich geometric texture. Elsewhere, in highreliefs, the edge constraint term also preserves depth discontinuities in the higher parts of the original scenes. The energy function can be discretized to obtain a sparse linear system. The reliefs are obtained by solving it by an iterative process. Finally, we apply non-linear compression to the relief to meet the user’s artistic needs. Experimental results show the method’s effectiveness for generating both bas- and high-reliefs for complex 3D scenes in a unified manner.

ENHANCED SECURITY FOR HOP BY HOP WIRELESS SENSOR NETWORK USING ELGAMAL ENCRYPTION ALGORITHM

The more modern network is unidirectional, also control of sensor activity, enabling. The WSN is built or even thousands of sensors of nodes, where each node is connected to on sensors. The sensor of the WSNs, from a simple star network to an advanced multi hop wireless mesh network can vary. The collecting of the data and controlling the node, may need to perform some successive on the measured data. Direct communication between individual nodes can also be required. The Task Manager Node (User) performs tasks in data storage, analysis and display. This proposed work empowers the intermediate nodes confirm the message with the goal that all corrupted message can be distinguished and dropped to save the sensor control. Hop by hop message security method for WSN without the edge constraint of the proficient. ElGamal encryption algorithm utilized in this work enables the semantic security. This framework successfully handles all sort of security issues. It likewise gives versatility, adaptable time authentication and source identity protection without any limitation on threshold.