In the field of 3D model matching and retrieval,an effective method for feature extraction is spherical harmonic or its mutations,and is acted on the spherical images.But the obtainment of spherical images from 3D mod...In the field of 3D model matching and retrieval,an effective method for feature extraction is spherical harmonic or its mutations,and is acted on the spherical images.But the obtainment of spherical images from 3D models is very time-consuming,which greatly restrains the responding speed of such systems.In this paper, we propose a quantitative evaluation of the whole process and give a detailed two-sided analysis based on the comparative size between pixels and voxels.The experiments show that the resultant optimized parameters are fit for the practical application and exhibit a satisfactory performance.展开更多
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
基金the National Natural Science Foundation of China(No.60903111)
文摘In the field of 3D model matching and retrieval,an effective method for feature extraction is spherical harmonic or its mutations,and is acted on the spherical images.But the obtainment of spherical images from 3D models is very time-consuming,which greatly restrains the responding speed of such systems.In this paper, we propose a quantitative evaluation of the whole process and give a detailed two-sided analysis based on the comparative size between pixels and voxels.The experiments show that the resultant optimized parameters are fit for the practical application and exhibit a satisfactory performance.
基金supported by the National Key Research and Development Project of China(2016YFC0303104)the National Natural Science Foundation of China(41304090)。
文摘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.
