• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.12
• /
• pp.1682-1687
• /
• 2020

We study the problem of sampling a subset of nodes of graphs for bandlimited graph signals such that the signal values on the sampled nodes provide the most information in order to reconstruct the original graph signal. Instead of directly minimizing the reconstruction error, we focus on minimizing the upper bound of the reconstruction error to reduce the complexity of the selection process. We further simplify the upper bound by applying useful approximations to propose a low-weight greedy selection process that is iteratively conducted to find a suboptimal sampling set. Through the extensive experiments for various graphs, we inspect the performance of the proposed algorithm by comparing with different sampling set selection methods and show that the proposed technique runs fast while preserving a competitive reconstruction performance, yielding a practical solution to real-time applications.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.16 no.1
• /
• pp.52-63
• /
• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.2 s.302
• /
• pp.113-120
• /
• 2005

3D reconstruction of a scene structure from un-calibrated image sequences has been long one of the central problems in computer vision. For 3D reconstruction in Euclidean space, projective reconstruction, which is classified into the merging method and the factorization, is needed as a preceding step. By calculating all camera projection matrices and structures at the same time, the factorization method suffers less from dia and error accumulation than the merging. However, the factorization is hard to analyze precisely long sequences because it is based on the assumption that all correspondences must remain in all views from the first frame to the last. This paper presents a new projective reconstruction method for recovery of 3D structure over long sequences. We break a full sequence into sub-sequences based on a quantitative measure considering the number of matching points between frames, the homography error, and the distribution of matching points on the frame. All of the projective reconstructions of sub-sequences are registered into the same coordinate frame for a complete description of the scene. no experimental results showed that the proposed method can recover more precise 3D structure than the merging method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.1
• /
• pp.38-42
• /
• 2002

A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.6
• /
• pp.58-66
• /
• 1997

This paper proposes a multiresolution surface parameter estimation method for range images. Based on robust estimation of surface parameters, it approximates a patch to a planar surface in the locally adaptive window. Selection of resolution is made pixelwise by comparing a locally computed homogeneity measure with th eglobal threshold determined by te distribution of the approximation error. The proposed multiresolution surface parameter estimation method is applied to range image reconstruction. Computer simulation results with noisy rnag eimages contaminated by additive gaussian noise and impulse noise show that the proposed multiresolution reconstruction method well preserves step and roof edges compared with the conventional methods. Also the segmentation method based on the estimated surface parameters is shown to be robust to noise.

• The Journal of the Korean dental association
• /
• v.52 no.10
• /
• pp.596-601
• /
• 2014

Computer-aided surgery is popular and useful in the field of oral and maxillofacial surgery, because of the possibility of simulation with a high accuracy. In all aspects of surgery, proper planning facilitates more predictable operative results, however before the use of virtual planning, much of this relied on 2-dimensional (2-D) imaging for treatment planning on a 3-dimensional (3-D) object and surgical trial and error. With real-time instrument positioning and clear anatomic identification, a computer-assisted navigation system (CANS) is exceptionally helpful in maxillofacial surgery. These techniques enable performing precise bony ablation and reconstruction, and also decrease surgical time and donor site defect.

• Proceedings of the IEEK Conference
• /
• 2000.11a
• /
• pp.505-508
• /
• 2000

The success of target reconstruction in SAR(Synthetic Aperture Radar) imaging system is greatly dependent on the coherent detection. Primary causes of incoherent detection are uncompensated target or sensor motion, random turbulence in propagation media, wrong path in radar platform, and etc. And these appear as multiplicative phase error to the echoed signal, which consequently, causes fatal degradations such as fading or dislocation of target image. In this paper, we present iterative phase error estimation scheme which uses echoed data in all temporal frequencies. We started with analyzing wave equation for one point target and extend to overall echoed data from the target scene - The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function. Eventually, this operation attains phase error correction algorithm from the total received SAR signal. We verify the success of the proposed algorithm by applying it to the simulated spotlight-mode SAR data.

• Journal of Biomedical Engineering Research
• /
• v.12 no.1
• /
• pp.43-48
• /
• 1991

As the computerized methods and equipments In nuclear medicine imaging increases, quantitative information is needed on the single photon emission computed tomographic Images as well as on the conventional nuclear medicine images. In this paper, the authors investigated the effect of several clinician - friendly reconstrution filters on the resultant transverse slices of backprojected Profiles of radioisotope distribution from the Quantitative point of view, and reduced the filter parameters such as cutoff frequency and order of filter which are neces mary to minimize the quantification error using computer-generated phantoms.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.921-923
• /
• 1999

In adaptive fuzzy control, fuzzy systems are used to approximate the unknown plant nonlinearities. However, because of the approximating error introduced into the feedback loop, it is difficult to guarantee the stability of the adaptive control algorithm. This paper presents a robust control algorithm against the reconstruction error and uniform boundedness of the all signals is estabilished in the Lyapunov sense.

• Smart Structures and Systems
• /
• v.25 no.3
• /
• pp.369-384
• /
• 2020

A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l₁-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.