• 한국전산유체공학회:학술대회논문집
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• 1999.05a
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• pp.98-105
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• 1999

The Pressure-based Unstructured-grid Navier-Stokes Solver PUNS-2/3D for incompressible steady and unsteady viscous flows has been developed. It is based on nonstaggered cell-centered finite volume method. Second-order upwind scheme with least-square reconstruction is used for convective fluxes. The SIMPLE method is implemented to couple the pressure and velocity fields. And the time derivatives in the momentum equations are discretised using a second-order Euler backward-differencing scheme. The discretised linear equations are solved by the preconditioned Biconjugate Gradient Stabilized method(Bi-CGSTAB). The developed solver is applied to validation problems using hybrid meshes.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.11
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• pp.3031-3040
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• 1995

Two-dimensional incompressible Navier-Stokes equations have been solved by the node-centered finite volume method with the unstructured triangular meshes. The pressure-velocity coupling is handled by the artificial compressibility algorithm due to its computational efficiency associated with the hyperbolic nature of the resulting equations. The convective fluxes are obtained by the Roe's flux difference splitting scheme using edge-based connectivities and higher-order differences are achieved by a reconstruction procedure. The time integration is based on an explicit four-stage Runge-Kutta scheme. Numerical procedures with local time stepping and implicit residual smoothing have been implemented to accelerate the convergence for the steady-state solutions. Comparisons with experimental data and other numerical results have proven accuracy and efficiency of the present unstructured approach.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.91-95
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• 2011

In this paper, we present an improved multi-scale gradient algorithm. The proposed algorithm works the effectively handling of both step and blurred edges. In the proposed algorithm, the image sharpening operator is sharpening the edges and contours of the objects. This operation gives an opportunity to get noise reduced image and step edged image. After that, multi-scale gradient operator works on noise reduced image in order to get a gradient image. The gradient image is segmented by watershed transform. The approach of region merging is used after watershed transform. The region merging is carried out according to the region area and region homogeneity. The region number of the proposed algorithm is 36% shorter than that of the existing algorithm because the proposed algorithm produces a few irrelevant regions. Moreover, the computational time of the proposed algorithm is relatively fast in comparison with the existing one.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.301-302
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• 2013

본 논문에서는 집적 영상(Integral imaging)에서 3차원 영상을 자유시점에서 재생하는 방법에 대해 설명한다. 집적 영상은 완전시차와 연속적인 시점을 제공하기 때문에 자유시점 재생을 사용하여 3차원 물체의 측면을 재생할 수 있다. 따라서, 이러한 3차원 데이터를 사용하여 보다 향상된 3차원 영상의 시각화 및 패턴 인식이 가능할 수 있다. 이를 증명하기 위해 컴퓨터 시뮬레이션을 수행하였다.

• Journal of the Korean Society of Visualization
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• v.18 no.3
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• pp.96-102
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• 2020

Oral cancer surgery changes the morphologic characteristics of the human upper airway. These changes can affect the flow patterns. In this study, computational fluid dynamics (CFD) simulations with transient solver were performed to numerically investigate the air flows in the human upper airways depending oral cancer surgery. 3D reconstructed models were obtained from 2D CT images of one patient. For the boundary condition, the realistic breathing cycle of human was applied. The hydraulic diameters of cross-sections for post-surgical model are changed greatly along streamwise direction, so these variations can cause higher wall shear stress and flow disturbance compared to pre-surgical model. The recirculation flows observed in the protruding region result in the relatively large pressure drop. These results can be helpful to understand the flow variations after resection surgery of oral cancer.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1083-1096
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• 2021

Compressed sensing-based matching pursuit algorithms can estimate the sparse channel of massive multiple input multiple-output systems with short pilot sequences. Although they have the advantages of low computational complexity and low pilot overhead, their accuracy remains insufficient. Simply multiplying the weight value and the estimated channel obtained in different iterations can only improve the accuracy of channel estimation under conditions of low signal-to-noise ratio (SNR), whereas it degrades accuracy under conditions of high SNR. To address this issue, an improved weighted matching pursuit algorithm is proposed, which obtains a suitable weight value u_op by training the channel data. The step of the weight value increasing with successive iterations is calculated according to the sparsity of the channel and u_op. Adjusting the weight value adaptively over the iterations can further improve the accuracy of estimation. The results of simulations conducted to evaluate the proposed algorithm show that it exhibits improved performance in terms of accuracy compared to previous methods under conditions of both high and low SNR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.89-98
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• 2000

This paper presents an active noise cancelling model using wavelet transform and subband filter banks based on adaptive filter. The analysis filter banks decompose input and error signals into QMF filter banks of lowpass and highpass bands. Each filter bank uses wavelet filter with dyadic tree structure. The decomposed input and error signals are iterated by adaptive filter coefficients of each subband using filtered-X LMS algorithm. The synthesis filter banks make output signal of wideband with perfect reconstruction to prepare adaptive filter output signals of each subband. The analysis and synthesis niter hants use conjugate quadrature filters for Pefect reconstruction. Also, The delayed LMS algorithm model for on-line identification of error path transfer characteristics is used gain and acoustic time delay factors. The proposed adaptive active noise cancelling modelis suggested by system retaining the computational and convergence speed advantage using wavelet subband filter banks.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.169-175
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• 2006

In this paper we propose a method of reconstruction of cylindrical panorama using simplified projective transform from the panning image on the fixed camera. For the practical construction of cylindrical panorama we consider the rotation of the camera on the Y-axis only, even though considering the rotation components on all of the X,Y,Z axis on three-dimensional space for projective transform between general panoramas. The restriction mentioned above simplifies projective transform with existing 8 degrees of freedom into the one with 4 degrees of freedom. In the results, overall computation for projective transform can be decreased to the great extents in quantify, because the number of corresponding points required for inducing the transforming formula is gone down by half. Proposed algorithm from the simulation carried out in this paper shows similar performance and decreased computational quantity compared with existing algorithm. Also, it shows the construction of cylindrical panorama using simplified projective transform.

• Advances in Computational Design
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• v.4 no.2
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• pp.155-177
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• 2019

Operation and Maintenance (O&M) phase is the main contributor to the total lifecycle cost of a building. Previous studies have described that Building Information Models (BIM), if available with detailed asset information and their properties, can enable rapid troubleshooting and execution of O&M tasks by providing the required information of the facility. Despite the potential benefits, there is still rarely BIM with Mechanical, Electrical and Plumbing (MEP) assets and properties that are available for O&M. BIM is usually not in possession for existing buildings and generating BIM manually is a time-consuming process. Hence, there is a need for an automated approach that can reconstruct the MEP systems in BIM. Previous studies investigated automatic reconstruction of BIM using architectural drawings, structural drawings, or the combination with photos. But most of the previous studies are limited to reconstruct the architectural and structural components. Note that mechanical components in the building typically require more frequent maintenance than architectural or structural components. However, the building mechanical drawings are relatively more complex due to various type of symbols that are used to represent the mechanical systems. In order to address this challenge, this paper proposed a symbol recognition framework that can automatically recognize the different type of symbols in the building mechanical drawings. This study applied vector-based computer vision techniques to recognize the symbols and their properties (e.g., location, type, etc.) in two vector-based input documents: 2D drawings and the symbol description document. The framework not only enables recognizing and locating the mechanical component of interest for BIM reconstruction purpose but opens the possibility of merging the updated information into the current BIM in the future reducing the time of repeated manual creation of BIM after every renovation project.