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基于局部坐标系法线投射的点云精细配准算法
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作者 蔡先杰 《现代计算机(中旬刊)》 2016年第9期57-62,共6页
点云配准是逆向工程中用于拼接点云模型的方法,可分为初始配准和精细配准两个步骤。假设在已经实现初始配准的情况下,提出基于局部坐标系法线投射的点云精细配准算法。通过对点云采样得到的采样点建立局部坐标系,然后将采样点的相邻点... 点云配准是逆向工程中用于拼接点云模型的方法,可分为初始配准和精细配准两个步骤。假设在已经实现初始配准的情况下,提出基于局部坐标系法线投射的点云精细配准算法。通过对点云采样得到的采样点建立局部坐标系,然后将采样点的相邻点集投影到该坐标系下,就可以得到代表模型的每个局部曲面的控制点集,再用法线投射算法求解出关联点对集并计算两个点云之间的变换参数(旋转角度和位移量)。局部坐标系法线投射算法获取到的关联点对有效性高,能明显减少迭代次数,提高配准效率。 展开更多
关键词 点云配准 精细配准 局部坐标系 法线投射 关联点对
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SPEEDING-UP RE-SAMPLED ALGORITHM IN RAY CASTING VOLUME RENDERING OF MEDICAL IMAGES
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作者 陶玲 王惠南 田芝亮 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2005年第1期52-58,共7页
Ray casting algorithm can obtain a better quality image in volume rendering, however, it exists some problems, such as powerful computing capacity and slow rendering speed. How to improve the re-sampled speed is a key... Ray casting algorithm can obtain a better quality image in volume rendering, however, it exists some problems, such as powerful computing capacity and slow rendering speed. How to improve the re-sampled speed is a key to speed up the ray casting algorithm. An algorithm is introduced to reduce matrix computation by matrix transformation characteristics of re-sampling points in a two coordinate system. The projection of 3-D datasets on image plane is adopted to reduce the number of rays. Utilizing boundary box technique avoids the sampling in empty voxel. By extending the Bresenham algorithm to three dimensions, each re-sampling point is calculated. Experimental results show that a two to three-fold improvement in rendering speed using the optimized algorithm, and the similar image quality to traditional algorithm can be achieved. The optimized algorithm can produce the required quality images, thus reducing the total operations and speeding up the volume rendering. 展开更多
关键词 volume rendering ray casting algorithm acceleration algorithm re-sampled algorithm
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A SPARSE PROJECTION CLUSTERING ALGORITHM 被引量:4
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作者 Xie Zongbo Feng Jiuchao 《Journal of Electronics(China)》 2009年第4期549-551,共3页
A clustering algorithm based on Sparse Projection (SP), called Sparse Projection Clus- tering (SPC), is proposed in this letter. The basic idea is applying SP to project the observed data onto a high-dimensional spars... A clustering algorithm based on Sparse Projection (SP), called Sparse Projection Clus- tering (SPC), is proposed in this letter. The basic idea is applying SP to project the observed data onto a high-dimensional sparse space, which is a nonlinear mapping with an explicit form and the K-means clustering algorithm can be therefore used to explore the inherent data patterns in the new space. The proposed algorithm is applied to cluster a complete artificial dataset and an incomplete real dataset. In comparison with the kernel K-means clustering algorithm, the proposed algorithm is more efficient. 展开更多
关键词 Sparse Projection Clustering (SPC) K-means clustering Kernel K-means clustering
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Fast forward modeling of muon transmission tomography based on model voxelization ray energy loss projection
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作者 Zhang Rong-Qing Xi Zhen-Zhu +2 位作者 Liu Wei Wang He Yang Zi-Yan 《Applied Geophysics》 SCIE CSCD 2022年第3期395-408,471,共15页
To solve the problems associated with low resolution and high computational effort infinite time,this paper proposes a fast forward modeling method for muon energy loss transmission tomography based on a model voxeliza... To solve the problems associated with low resolution and high computational effort infinite time,this paper proposes a fast forward modeling method for muon energy loss transmission tomography based on a model voxelization energy loss projection algorithm.First,the energy loss equation for muon transmission tomography is derived from the Bethe–Bloch formula,and the imaging region is then dissected into several units using the model voxelization method.Thereafter,the three-dimensional(3-D)imaging model is discretized into parallel and equally spaced two-dimensional(2-D)slices using the model layering method to realize a dimensional reduction of the 3-D volume data and accelerate the forward calculation speed.Subsequently,the muon energy loss transmission tomography equation is discretized using the ray energy loss projection method to establish a set of energy loss equations for the muon penetration voxel model.Finally,the muon energy loss values at the outgoing point are obtained by solving the projection coefficient matrix of the ray length-weighted model,achieving a significant reduction in the number of muons and improving the computational efficiency.A comparison of our results with the simulation results based on the Monte Carlo method verifies the accuracy and effectiveness of the algorithm proposed in this paper.The metallic mineral identification tests show that the proposed algorithm can quickly identify high-density metallic minerals.The muon energy loss response can accurately identify the boundary of the anomalies and their spatial distribution characteristics. 展开更多
关键词 Muon transmission tomography model voxelization ray energy loss projection fast forward modeling Monte Carlo simulation
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