• 제목/요약/키워드: Reconstruction Algorithm

검색결과 992건 처리시간 0.023초

3차원 충돌해석 정보를 이용한 측면 충돌 사고 재구성 (A Study on the Side Collision Accident Reconstruction Using 3-Dimensional Crash Analysis)

  • 장인식;김일동
    • 한국자동차공학회논문집
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    • 제16권1호
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    • pp.52-63
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    • 2008
  • The side collision reconstruction algorithm is developed using three dimensional car crash analysis. Medium size passenger car is modeled for finite element analysis. Total 24 side collision configurations, four different speed and six different angle, are set up for making side collision database. Deformation index and degree index are built up for each collision case. Deformation index is a kind of deformation estimate averaging displacement of side door of crashed car from finite element analysis result. Angle index is constructed measuring deformed angle of crashing car. There are two kinds of angle index, one is measured at driver's side and the other is measured at passenger's side. Also a collision analysis information in side of cars is used for giving a basis for scientific and practical reason in a reconstruction of the car accident. The analysis program, LS-DYNA3D is utilized for finite element analysis program for a collision analysis. Those database are used for side collision reconstruction. Side collision reconstruction algorithm is developed, and applied to find the collision conditions before the accident occurs. Three example collision cases are tried to check the effectiveness of the algorithm. Deformation index and angle index is extracted for the case from the analysis result. Deformation index is compared to the established database, and estimated collision speed and angle are introduced by interpolation function. Angle index is used to select a specific collision condition from the several available conditions. The collision condition found by reconstruction algorithm shows good match with original condition within 10% error for speed and angle. As a result, the calculation from the reconstruction of the situation is reproducing the situation well. The performance in this study can be used in many ways for practical field using deformation index and degree index. Other different collision situations may be set up for extending the scope of this study in the future.

지능 최적 알고리즘을 이용한 전기임피던스 단층촬영법의 영상복원 (Intelligent Optimization Algorithm Approach to Image Reconstruction in Electrical Impedance Tomography)

  • 김호찬;부창친;이윤준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.513-516
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    • 2002
  • In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.

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An Efficient Model Based on Smoothed ℓ0 Norm for Sparse Signal Reconstruction

  • Li, Yangyang;Sun, Guiling;Li, Zhouzhou;Geng, Tianyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.2028-2041
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    • 2019
  • Compressed sensing (CS) is a new theory. With regard to the sparse signal, an exact reconstruction can be obtained with sufficient CS measurements. Nevertheless, in practical applications, the transform coefficients of many signals usually have weak sparsity and suffer from a variety of noise disturbances. What's worse, most existing classical algorithms are not able to effectively solve this issue. So we proposed an efficient algorithm based on smoothed ${\ell}_0$ norm for sparse signal reconstruction. The direct ${\ell}_0$ norm problem is NP hard, but it is unrealistic to directly solve the ${\ell}_0$ norm problem for the reconstruction of the sparse signal. To select a suitable sequence of smoothed function and solve the ${\ell}_0$ norm optimization problem effectively, we come up with a generalized approximate function model as the objective function to calculate the original signal. The proposed model preserves sharper edges, which is better than any other existing norm based algorithm. As a result, following this model, extensive simulations show that the proposed algorithm is superior to the similar algorithms used for solving the same problem.

Research on Reconstruction Technology of Biofilm Surface Based on Image Stacking

  • Zhao, Yuyang;Tao, Xueheng;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제24권11호
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    • pp.1472-1480
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    • 2021
  • Image stacking technique is one of the key techniques for complex surface reconstruction. The process includes sample collection, image processing, algorithm editing, surface reconstruction, and finally reaching reliable conclusions. Since this experiment is based on laser scanning confocal microscope to collect the original contour information of the sample, it is necessary to briefly introduce the relevant principle and operation method of laser scanning confocal microscope. After that, the original image is collected and processed, and the data is expanded by interpolation method. Meanwhile, several methods of surface reconstruction are listed. After comparing the advantages and disadvantages of each method, one-dimensional interpolation and volume rendering are finally used to reconstruct the 3D model. The experimental results show that the final 3d surface modeling is more consistent with the appearance information of the original samples. At the same time, the algorithm is simple and easy to understand, strong operability, and can meet the requirements of surface reconstruction of different types of samples.

CT Image Reconstruction of Wood Using Ultrasound Velocities I - Effects of Reconstruction Algorithms and Wood Characteristics -

  • Kim, Kwang-Mo;Lee, Jun-Jae
    • Journal of the Korean Wood Science and Technology
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    • 제33권5호통권133호
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    • pp.21-28
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    • 2005
  • For the proper conservation of wooden cultural properties, non-destructive evaluation (NDE) method, which can be used to quantitatively evaluate the internal state of wood members, are needed. In this study, an ultrasonic CT system composed of portable devices was attempted, and the capacity of this system was verified by reconstructing the CT images for two phantoms and two artificially defected specimens. Results from this study showed that the sizes of detected defects were enlarged and the shapes were distorted on the CT images. Also, the positions were shifted somewhat toward the surface of specimen, which is regarded due to the anisotropic property of wood. Compared to the filtered back-projection method, SIRT (simultaneous iterative reconstruction technique) method was determined to be more efficient as the algorithm of image reconstruction for wood. A new ultrasonic CT system is thought to be used as a NDE method for wood. However wood characteristics and wave diffraction within wood made it difficult to accurately evaluate the size, shape and position of defects. To improve the quality of CT image of wood, more research including the relationship between wood and ultrasound is needed, and wood properties should be taken into consideration on the image reconstruction algorithm.

Filtered Backprojection에서 정착자를 사용한 고주파 감쇠 (The Use of Regularizers for High-Frequency Apodization in Filtered Backprojection)

  • 이수진;김용호
    • 공학논문집
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    • 제2권1호
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    • pp.49-56
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    • 1997
  • Emission computed tomography에 있어서 Bayesian방법에 근거한 통계학적 영상 재구성법이 수년간에 걸쳐 중요한 관심사로 대두되어 왔다. 이는 Bayesian 접근 방법을 사용할 경우 영상 재구성 알고리즘에 재구성하고자 하는 영상에 대한 사전정보를 포함시킬 수 있기 때문이었다. 이러한 방법은 경우에 따라 향상된 성능을 보이고 있으나, 막대한 계산시간으로 인해 실제 임상에 적용되기가 매우 어려운 상황이다. 한편, filtered backprojection(FBP)은 알고리즘 자체가 간단하고 계산시간도 매우 단축되므로 대부분의 임상에 널리 적용되고 있다. 본 연구에서는 Bayesian 영상 재구성에서 매우 유용하게 사용되는 spline 모델을 FBP의 고주파 감쇠를 위한 정칙자로 사용함으로써 FBP 영상 재구성에 Bayesian 방법과 유사한 효과를 얻을 수 있음을 보인다.

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Sparse-View CT Image Recovery Using Two-Step Iterative Shrinkage-Thresholding Algorithm

  • Chae, Byung Gyu;Lee, Sooyeul
    • ETRI Journal
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    • 제37권6호
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    • pp.1251-1258
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    • 2015
  • We investigate an image recovery method for sparse-view computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other first-order methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm -sing measured projection data.

개선된 FBP 토모그라픽 알고리즘에서 분해능의 결정 (The Determination of Resolution on the Improved FBP Tomographic Algorithm)

  • 구길모;황기환;박치승;고덕영
    • 대한전자공학회논문지TE
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    • 제42권1호
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    • pp.21-28
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    • 2005
  • 본 논문은 토모그라픽 영상시스템에 적합한 FBP 토모그라픽 영상복원 알고리즘의 분해능에 관하여 연구하였다. 고정좌표계를 이용하는 개선된 FBP 토모그라픽 영상복원 알고리즘으로부터 분해능을 분석할 수 있는 모호함수를 유도하였고, 이를 이용한 모의실험을 통하여 얻은 진폭분포로부터 측방향 및 축방향 분해능을 정량적으로 결정하였다. 개선된 FBP 토모그라픽 영상복원 알고리즘을 통해 기존의 SAM(Scanning Acoustic Microscope)시스템으로부터 얻을 수 있는 3dB와 6dB 축방향 분해능에 대해서도 각각 0.70 파장과 0.96 파장으로 SAM 영상의 3dB 축방향 분해능인 7 파장에 비하여 매우 개선된 분해능을 얻을 수 있음을 확인하였다. 평면 입사파의 회절 토모그라픽 영상복원을 위한 개선된 FBP 토모그라픽 영상복원 알고리즘은 미세하고 복잡한 다층 박막구조를 갖는 시료에 대하여 좋은 분해능을 갖는 토모그라픽 영상시스템을 개발하는데 유용하게 활용할 수 있도록 하였다.

EIT Image Reconstruction by Simultaneous Perturbation Method

  • Kim, Ho-Chan;Boo, Chang-Jin;Lee, Yoon-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.159-164
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    • 2004
  • In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simultaneous perturbation method as an image reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

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Shrink-Wrapped Boundary Face Algorithm for Mesh Reconstruction from Unorganized Points

  • Koo, Bon-Ki;Choi, Young-Kyu;Chu, Chang-Woo;Kim, Jae-Chul;Choi, Byoung-Tae
    • ETRI Journal
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    • 제27권2호
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    • pp.235-238
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    • 2005
  • A new mesh reconstruction scheme for approximating a surface from a set of unorganized 3D points is proposed. The proposed method, called a shrink-wrapped boundary face (SWBF) algorithm, produces the final surface by iteratively shrinking the initial mesh generated from the definition of the boundary faces. SWBF surmounts the genus-0 spherical topology restriction of previous shrink-wrapping-based mesh generation techniques and can be applied to any type of surface topology. Furthermore, SWBF is significantly faster than a related algorithm of Jeong and others, as SWBF requires only a local nearest-point-search in the shrinking process. Our experiments show that SWBF is very robust and efficient for surface reconstruction from an unorganized point cloud.

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