针对现有水果识别方法需大量水果样本学习或仅对单一特征进行识别而导致的识别率较低的问题,提出一种基于水果图像处理的水果颜色和形状特征参数的提取方法、基于灰色关联分析和模糊隶属度匹配的球形水果自动识别方法。该方法通过提取...针对现有水果识别方法需大量水果样本学习或仅对单一特征进行识别而导致的识别率较低的问题,提出一种基于水果图像处理的水果颜色和形状特征参数的提取方法、基于灰色关联分析和模糊隶属度匹配的球形水果自动识别方法。该方法通过提取水果图像关注区域(region of interest,ROI)的颜色和形状特征,建立参比水果的颜色特征参比数据库和形状特征隶属度函数,计算待识别水果与参比水果颜色特征的灰色加权关联度,求取待识别水果对于参比水果形状特征参数的模糊隶属度,按各特征量等权的原则合成待识别水果对参比水果的总匹配度,并根据总匹配度的大小实现待识别水果种类的判别。大量实验结果表明:该方法简单、有效,不需要大样本量水果的学习和训练,平均识别正确率达到99%以上。展开更多
Point cloud registration is an essential step in the process of 3D reconstruction.In this paper,a fast registration algorithm of rock mass point cloud is proposed based on the improved iterative closest point (ICP)alg...Point cloud registration is an essential step in the process of 3D reconstruction.In this paper,a fast registration algorithm of rock mass point cloud is proposed based on the improved iterative closest point (ICP)algorithm.In our proposed algorithm,the point cloud data of single station scanner is transformed into digital images by spherical polar coordinates,then image features are extracted and edge points are removed,the features used in this algorithm is scale-invariant feature transform (SIFT).By analyzing the corresponding relationship between digital images and 3D points,the 3D feature points are extracted,from which we can search for the two-way correspondence as candidates. After the false matches are eliminated by the exhaustive search method based on random sampling,the transformation is computed via the Levenberg-Marquardt-Iterative Closest Point (LM-ICP)algorithm.Experiments on real data of rock mass show that the proposed algorithm has the similar accuracy and better registration efficiency compared with the ICP algorithm and other algorithms.展开更多
Over the last two decades,stochastic optimization algorithms have proved to be a very promising approach to solving a variety of complex optimization problems.Bald eagle search optimization(BES)as a new stochastic opt...Over the last two decades,stochastic optimization algorithms have proved to be a very promising approach to solving a variety of complex optimization problems.Bald eagle search optimization(BES)as a new stochastic optimization algorithm with fast convergence speed has the ability of prominent optimization and the defect of collapsing in the local best.To avoid BES collapse at local optima,inspired by the fact that the volume of the sphere is the largest when the surface area is certain,an improved bald eagle search optimization algorithm(INMBES)integrating the random shrinkage mechanism of the sphere is proposed.Firstly,the INMBES embeds spherical coordinates to design a more accurate parameter update method to modify the coverage and dispersion of the population.Secondly,the population splits into elite and non-elite groups and the Bernoulli chaos is applied to elite group to tap around potential solutions of the INMBES.The non-elite group is redistributed again and the Nelder-Mead simplex strategy is applied to each group to accelerate the evolution of the worst individual and the convergence process of the INMBES.The results of Friedman and Wilcoxon rank sum tests of CEC2017 in 10,30,50,and 100 dimensions numerical optimization confirm that the INMBES has superior performance in convergence accuracy and avoiding falling into local optimization compared with other potential improved algorithms but inferior to the champion algorithm and ranking third.The three engineering constraint optimization problems and 26 real world problems and the problem of extracting the best feature subset by encapsulated feature selection method verify that the INMBES’s performance ranks first and has achieved satisfactory accuracy in solving practical problems.展开更多
The high porosity and interconnectivity of scaffolds are critical for nutrient transmission in bone tis-sue engineering but usually lead to poor mechanical properties.Herein,a novel method that combines acid etching(A...The high porosity and interconnectivity of scaffolds are critical for nutrient transmission in bone tis-sue engineering but usually lead to poor mechanical properties.Herein,a novel method that combines acid etching(AE)with selective laser sintering(SLS)and reaction bonding(RB)of Al particles is pro-posed to realize highly improved porosity,interconnectivity,mechanical strength,and in vitro bioactivity in 3D Al_(2)O_(3) scaffolds.By controlling the oxidation and etching behaviors of Al particles,a tunable hol-low spherical feature can be obtained,which brings about the distinction in compressive response and fracture path.The prevention of microcrack propagation on the in situ formed hollow spheres results in unique near elastic buckling rather than traditional brittle fracture,allowing an unparalleled compressive strength of 3.72±0.17 MPa at a high porosity of 87.7%±0.4%and pore interconnectivity of 94.7%±0.4%.Furthermore,scaffolds with an optimized pore structure and superhydrophilic surface show excellent cell proliferation and adhesion properties.Our findings offer a promising strategy for the coexistence of out-standing mechanical and biological properties,with great potential for tissue engineering applications.展开更多
In this paper a novel 3D model retrieval method that employs multi-level spherical moment analysis and relies on voxelization and spherical mapping of the 3D models is proposed. For a given polygon-soup 3D model, firs...In this paper a novel 3D model retrieval method that employs multi-level spherical moment analysis and relies on voxelization and spherical mapping of the 3D models is proposed. For a given polygon-soup 3D model, first a pose normalization step is done to align the model into a canonical coordinate frame so as to define the shape representation with respect to this orientation. Afterward we rasterize its exterior surface into cubical voxel grids, then a series of homocentric spheres with their center superposing the center of the voxel grids cut the voxel grids into several spherical images. Finally moments belonging to each sphere are computed and the moments of all spheres constitute the descriptor of the model. Experiments showed that Euclidean distance based on this kind of feature vector can distinguish different 3D models well and that the 3D model retrieval system based on this arithmetic yields satisfactory performance.展开更多
文摘针对现有水果识别方法需大量水果样本学习或仅对单一特征进行识别而导致的识别率较低的问题,提出一种基于水果图像处理的水果颜色和形状特征参数的提取方法、基于灰色关联分析和模糊隶属度匹配的球形水果自动识别方法。该方法通过提取水果图像关注区域(region of interest,ROI)的颜色和形状特征,建立参比水果的颜色特征参比数据库和形状特征隶属度函数,计算待识别水果与参比水果颜色特征的灰色加权关联度,求取待识别水果对于参比水果形状特征参数的模糊隶属度,按各特征量等权的原则合成待识别水果对参比水果的总匹配度,并根据总匹配度的大小实现待识别水果种类的判别。大量实验结果表明:该方法简单、有效,不需要大样本量水果的学习和训练,平均识别正确率达到99%以上。
基金the National Natural Science Foundation of China (Grant No.61471338)Youth Innovation Promotion Association CAS (2015361)+2 种基金Key Research Program of Frontier Sciences,CAS (QYZDY-SSW-SYS004)Beijing Nova Program (z171100001117048)President Fund of UCAS.
文摘Point cloud registration is an essential step in the process of 3D reconstruction.In this paper,a fast registration algorithm of rock mass point cloud is proposed based on the improved iterative closest point (ICP)algorithm.In our proposed algorithm,the point cloud data of single station scanner is transformed into digital images by spherical polar coordinates,then image features are extracted and edge points are removed,the features used in this algorithm is scale-invariant feature transform (SIFT).By analyzing the corresponding relationship between digital images and 3D points,the 3D feature points are extracted,from which we can search for the two-way correspondence as candidates. After the false matches are eliminated by the exhaustive search method based on random sampling,the transformation is computed via the Levenberg-Marquardt-Iterative Closest Point (LM-ICP)algorithm.Experiments on real data of rock mass show that the proposed algorithm has the similar accuracy and better registration efficiency compared with the ICP algorithm and other algorithms.
基金supported by the National Natural Science Foundation of China No.61976176.
文摘Over the last two decades,stochastic optimization algorithms have proved to be a very promising approach to solving a variety of complex optimization problems.Bald eagle search optimization(BES)as a new stochastic optimization algorithm with fast convergence speed has the ability of prominent optimization and the defect of collapsing in the local best.To avoid BES collapse at local optima,inspired by the fact that the volume of the sphere is the largest when the surface area is certain,an improved bald eagle search optimization algorithm(INMBES)integrating the random shrinkage mechanism of the sphere is proposed.Firstly,the INMBES embeds spherical coordinates to design a more accurate parameter update method to modify the coverage and dispersion of the population.Secondly,the population splits into elite and non-elite groups and the Bernoulli chaos is applied to elite group to tap around potential solutions of the INMBES.The non-elite group is redistributed again and the Nelder-Mead simplex strategy is applied to each group to accelerate the evolution of the worst individual and the convergence process of the INMBES.The results of Friedman and Wilcoxon rank sum tests of CEC2017 in 10,30,50,and 100 dimensions numerical optimization confirm that the INMBES has superior performance in convergence accuracy and avoiding falling into local optimization compared with other potential improved algorithms but inferior to the champion algorithm and ranking third.The three engineering constraint optimization problems and 26 real world problems and the problem of extracting the best feature subset by encapsulated feature selection method verify that the INMBES’s performance ranks first and has achieved satisfactory accuracy in solving practical problems.
文摘The high porosity and interconnectivity of scaffolds are critical for nutrient transmission in bone tis-sue engineering but usually lead to poor mechanical properties.Herein,a novel method that combines acid etching(AE)with selective laser sintering(SLS)and reaction bonding(RB)of Al particles is pro-posed to realize highly improved porosity,interconnectivity,mechanical strength,and in vitro bioactivity in 3D Al_(2)O_(3) scaffolds.By controlling the oxidation and etching behaviors of Al particles,a tunable hol-low spherical feature can be obtained,which brings about the distinction in compressive response and fracture path.The prevention of microcrack propagation on the in situ formed hollow spheres results in unique near elastic buckling rather than traditional brittle fracture,allowing an unparalleled compressive strength of 3.72±0.17 MPa at a high porosity of 87.7%±0.4%and pore interconnectivity of 94.7%±0.4%.Furthermore,scaffolds with an optimized pore structure and superhydrophilic surface show excellent cell proliferation and adhesion properties.Our findings offer a promising strategy for the coexistence of out-standing mechanical and biological properties,with great potential for tissue engineering applications.
基金Project (No. 60573146) supported by the National Natural Science Foundation of China
文摘In this paper a novel 3D model retrieval method that employs multi-level spherical moment analysis and relies on voxelization and spherical mapping of the 3D models is proposed. For a given polygon-soup 3D model, first a pose normalization step is done to align the model into a canonical coordinate frame so as to define the shape representation with respect to this orientation. Afterward we rasterize its exterior surface into cubical voxel grids, then a series of homocentric spheres with their center superposing the center of the voxel grids cut the voxel grids into several spherical images. Finally moments belonging to each sphere are computed and the moments of all spheres constitute the descriptor of the model. Experiments showed that Euclidean distance based on this kind of feature vector can distinguish different 3D models well and that the 3D model retrieval system based on this arithmetic yields satisfactory performance.
