Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effect...Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effectively works in calculating the volume of the point cloud of the spatial object obtained through three-dimensional laser scanning(3DLS).In this method,a uniformly spaced sequent slicing process is first conducted in a specific direction on the point cloud of the spatial object obtained through 3DLS.A series of discrete point cloud slices corresponding to the point cloud bodies are then obtained.Subsequently,the outline boundary polygon of the point cloud slicing is searched one by one in accordance with the slicing sequence and areas of the polygon.The point cloud slice is also calculated.Finally,the individual point cloud section volume is calculated through the slicing areas and the adjacent slicing gap.Thus,the total volume of the scanned spatial object can be calculated by summing up the individual volumes.According to the results and analysis of the calculated examples,the slice-based volume-calculating method for the point cloud of irregular objects obtained through 3DLS is correct,concise in process,reliable in results,efficient in calculation methods,and controllable on accuracy.This method comes as a good solution to the volume calculation of irregular objects.展开更多
Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaptio...Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.展开更多
An improved X-ray apparatus that combines tensile testing and X-ray diffraction has been designed and constructed to conduct timeresolved experiments during uniaxial stretching.By utilizing mortise-like clamping jaws ...An improved X-ray apparatus that combines tensile testing and X-ray diffraction has been designed and constructed to conduct timeresolved experiments during uniaxial stretching.By utilizing mortise-like clamping jaws and dogbone-shaped specimens,this setup allows for the simultaneous recording of high-quality mechanical responses and 2D diffraction patterns due to the minimization of experimental errors from sample slippage or premature fracture.Furthermore,the local extension ratio can be accurately determined based on thickness variation,and the Hermans'orientation function was demonstrated to be a reliable method with high accuracy to calculate the segmental orientation parameter〈P_(2)〉in elastomeric samples under high degree of stretching.In summary,this innovative tensile-WAXD instrument has proven to be a promising and powerful technique for investigating the“stress-deformation-segmental orientation”relationship in elastomers with high extensibilities.展开更多
Attribute reduction is an important process in rough set theory.Finding minimum attribute reduction has been proven to help the user-oriented make better knowledge discovery in some cases.In this paper,an efficient mi...Attribute reduction is an important process in rough set theory.Finding minimum attribute reduction has been proven to help the user-oriented make better knowledge discovery in some cases.In this paper,an efficient minimum attribute reduction algorithm is proposed based on the multilevel evolutionary tree with self-adaptive subpopulations.A model of multilevel evolutionary tree with self-adaptive subpopulations is constructed,and interacting attribute sets are better decomposed into subsets by the self-adaptive mechanism of elitist populations.Moreover it can self-adapt the subpopulation sizes according to the historical performance record so that interacting attribute decision variables are captured into the same grouped subpopulation,which will be extended to better performance in both quality of solution and competitive computation complexity for minimum attribute reduction.The conducted experiments show the proposed algorithm is better on both efficiency and accuracy of minimum attribute reduction than some representative algorithms.Finally the proposed algorithm is applied to magnetic resonance image(MRI)segmentation,and its stronger applicability is further demonstrated by the effective and robust segmentation results.展开更多
为使桥梁病害检测更加高效、客观和智能,提出一种自动识别并定量计算混凝土病害尺寸的方法。该方法采用视觉几何组网络(Visual Geometry Group Network,VGG)作为U形网络(U-Net)的主干网络,对混凝土病害(剥落、裂缝和露筋)图像进行语义分...为使桥梁病害检测更加高效、客观和智能,提出一种自动识别并定量计算混凝土病害尺寸的方法。该方法采用视觉几何组网络(Visual Geometry Group Network,VGG)作为U形网络(U-Net)的主干网络,对混凝土病害(剥落、裂缝和露筋)图像进行语义分割,采用数学形态学算法对图像中的病害区域进行优化。通过MATLAB软件计算得到优化后的分割图像中病害区域像素点的数量,并利用参照物标定出图像中单个像素点的尺寸,计算得到混凝土病害的面积(或长度)。采用该方法对河南省许昌市17座现役钢筋混凝土桥梁病害图像进行语义分割实验。结果表明:U-Net能以较高的精度对复杂背景下混凝土桥梁多类病害进行像素级的分类,类别平均像素准确率为90.53%,平均交并比为80.54%。使用数学形态学对语义分割图像进行优化后,计算精度明显提高,优化后的误差绝对值为0.08%~0.21%。展开更多
文摘Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effectively works in calculating the volume of the point cloud of the spatial object obtained through three-dimensional laser scanning(3DLS).In this method,a uniformly spaced sequent slicing process is first conducted in a specific direction on the point cloud of the spatial object obtained through 3DLS.A series of discrete point cloud slices corresponding to the point cloud bodies are then obtained.Subsequently,the outline boundary polygon of the point cloud slicing is searched one by one in accordance with the slicing sequence and areas of the polygon.The point cloud slice is also calculated.Finally,the individual point cloud section volume is calculated through the slicing areas and the adjacent slicing gap.Thus,the total volume of the scanned spatial object can be calculated by summing up the individual volumes.According to the results and analysis of the calculated examples,the slice-based volume-calculating method for the point cloud of irregular objects obtained through 3DLS is correct,concise in process,reliable in results,efficient in calculation methods,and controllable on accuracy.This method comes as a good solution to the volume calculation of irregular objects.
基金supported by the China Postdoctoral Science Foundation under Grant No.2015M571993the Shandong Provincial Natural Science Foundation,China under Grant No.ZR2017MD004+1 种基金the National Natural Science Foundation of China under Grant No.61602269Qingdao Postdoctoral Application Research Funded Project
文摘Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.
基金financial support of China CSC Scholarship(No.201604910522).
文摘An improved X-ray apparatus that combines tensile testing and X-ray diffraction has been designed and constructed to conduct timeresolved experiments during uniaxial stretching.By utilizing mortise-like clamping jaws and dogbone-shaped specimens,this setup allows for the simultaneous recording of high-quality mechanical responses and 2D diffraction patterns due to the minimization of experimental errors from sample slippage or premature fracture.Furthermore,the local extension ratio can be accurately determined based on thickness variation,and the Hermans'orientation function was demonstrated to be a reliable method with high accuracy to calculate the segmental orientation parameter〈P_(2)〉in elastomeric samples under high degree of stretching.In summary,this innovative tensile-WAXD instrument has proven to be a promising and powerful technique for investigating the“stress-deformation-segmental orientation”relationship in elastomers with high extensibilities.
基金Supported by the National Natural Science Foundation of China(61139002,61171132)the Natural Science Foundation of Jiangsu Education Department(12KJB520013)+2 种基金the Fundamental Research Funds for the Central Universitiesthe Funding of Jiangsu Innovation Program for Graduate Education(CXZZ110219)the Open Project Program of State Key Lab for Novel Software Technology in Nanjing University(KFKT2012B28)
文摘Attribute reduction is an important process in rough set theory.Finding minimum attribute reduction has been proven to help the user-oriented make better knowledge discovery in some cases.In this paper,an efficient minimum attribute reduction algorithm is proposed based on the multilevel evolutionary tree with self-adaptive subpopulations.A model of multilevel evolutionary tree with self-adaptive subpopulations is constructed,and interacting attribute sets are better decomposed into subsets by the self-adaptive mechanism of elitist populations.Moreover it can self-adapt the subpopulation sizes according to the historical performance record so that interacting attribute decision variables are captured into the same grouped subpopulation,which will be extended to better performance in both quality of solution and competitive computation complexity for minimum attribute reduction.The conducted experiments show the proposed algorithm is better on both efficiency and accuracy of minimum attribute reduction than some representative algorithms.Finally the proposed algorithm is applied to magnetic resonance image(MRI)segmentation,and its stronger applicability is further demonstrated by the effective and robust segmentation results.
文摘为使桥梁病害检测更加高效、客观和智能,提出一种自动识别并定量计算混凝土病害尺寸的方法。该方法采用视觉几何组网络(Visual Geometry Group Network,VGG)作为U形网络(U-Net)的主干网络,对混凝土病害(剥落、裂缝和露筋)图像进行语义分割,采用数学形态学算法对图像中的病害区域进行优化。通过MATLAB软件计算得到优化后的分割图像中病害区域像素点的数量,并利用参照物标定出图像中单个像素点的尺寸,计算得到混凝土病害的面积(或长度)。采用该方法对河南省许昌市17座现役钢筋混凝土桥梁病害图像进行语义分割实验。结果表明:U-Net能以较高的精度对复杂背景下混凝土桥梁多类病害进行像素级的分类,类别平均像素准确率为90.53%,平均交并比为80.54%。使用数学形态学对语义分割图像进行优化后,计算精度明显提高,优化后的误差绝对值为0.08%~0.21%。
