• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.925-936
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• 2009

There very many approaches to impute missing values in the iid. case. However, it is hardly found the imputation techniques in the Markov random field(MRF) case. In this paper, we show that the imputation under MRF is just to impute by fitting the normal mixture model(NMM) under several practical assumptions. Our multivariate normal mixture model based approaches under MRF is applied to impute the missing pixel values of 3-variate (R, G, B) color image, providing a technique to smooth the imputed values.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.511-516
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• 2004

수치표고모델, 정사영상과 같은 공간영상정보를 구축하기 위해서는 입체영상을 이동한 영상정합(image matching)의 과정이 필수적이며, 단영상 또는 스테레오 영상을 이용하여 대상물의 3차원 정보를 재구성하고 복원하는 기술은 사진측량 및 컴퓨터 비전 분야의 주요 연구 중의 하나이다. 본 연구에서는 화소값의 유사성과 상호관계성을 고려하는 MRF 모델을 이용하여 영상정합을 수행하였다. MRF 모델은 공간분석이나 물리적 현상의 전후관계(contextural dependencies)의 분석을 위한 확률이론의 한 분야로 다양한 공간정보를 통합할 수 있는 방법을 제공한다. 본 연구에서는 기준영상의 화소에 시차를 할당하는 접근 방법으로 확률모델의 일종인 마르코프 랜덤필드(MRF)모델에 기반한 영상정합기법을 제안하였고, 공간내 화소의 상호관계를 고려해주므로 대상물의 경계부분에서의 매칭 정확도를 향상시켰다. 영상정합문제에서의 MRF 기본가정은 영상 내 특정화소의 시차는 그 주위화소의 시차에 의한 부분정보에 따라 결정이 가능하다는 것이다. 깁스분포(gibbs distribution)를 사용하여 사후(posteriori) 확률값을 유도해내고, 이를 최대사후확률(MAP: Maximum a Posteriori)추정법을 이용하여 에너지함수를 생성하였다. 생성된 에너지함수의 최적화(Optimization)를 위하여 본 연구에서는 전역최적화기법인 multiway cut 기법을 사용하여 영상정합에 있어 에너지함수를 최소로 하는 이미지화소에 대한 시차레이블을 구하여 영상정합을 수행하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.54-63
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• 2007

The purpose of this study is to present a new energy minimization method for image completion with hierarchical approach. The goal of image completion is to fill in missing part in a possibly large region of an image so that a visually plausible outcome is obtained. An exemplar-based Markov Random Field Modeling(MRF) is proposed in this paper. This model can deal with following problems; detection of global features, flexibility on environmental changes, reduction of computational cost, and generic extension to other related domains such as image inpainting. We use the Priority Belief Propagation(Priority-BP) which is a kind of Belief propagation(BP) algorithms for the optimization of MRF. We propose the hierarchical Priority-BP that reduces the number of nodes in MRF and to apply hierarchical propagation of messages for image completion. We show that our approach which uses hierarchical Priority-BP algorithm in image completion works well on a number of examples.

• Coupled systems mechanics
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• v.7 no.6
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• pp.731-753
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• 2018

The recent seismic events have led to concerns on safety and vulnerability of Reinforced Concrete Moment Resisting Frame "RC-MRF" buildings. The seismic design demands are greatly dependent on the computational tools, the inherent assumptions and approximations introduced in the modeling process. Thus, it is essential to assess the relative importance of implementing different modeling approaches and investigate the computed response sensitivity to the corresponding modeling assumptions. Many parameters and assumptions are to be justified for generation effective and accurate structural models of RC-MRF buildings to simulate the lateral response and evaluate seismic design demands. So, the present study aims to develop reliable finite element model through many refinements in modeling the various structural components. The effect of finite element modeling assumptions, analysis methods and code provisions on seismic response demands for the structural design of RC-MRF buildings are investigated. where, a series of three-dimensional finite element models were created to study various approaches to quantitatively improve the accuracy of FE models of symmetric buildings located in active seismic zones. It is shown from results of the comparative analyses that the use of a calibrated frame model which was made up of line elements featuring rigid offsets manages to provide estimates that match best with estimates obtained from a much more rigorous modeling approach involving the use of shell elements.

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.39-44
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• 2005

To validate the rotor performance analysis, 3D Computational Fluid Dynamics(CFD) analysis was performed for tilt rotor aeroacoustic model(TRAM). Also, 3D vehicle with rotating rotors was simulated for rotor power effect analysis. Multiple reference frame(MRF) and sliding mesh techniques were implemented to capture the effect of rotor revolution. CFD results were compared with the wind tunnel test results to validate their accuracy. At helicopter mode, CFD analysis predicted lower thrust than the wind tunnel test but CFD results showed good agreement with the test result at cruise mode. Rotor power effect decreased the lift but did not change drag and pitching moment.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.553-555
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• 2001

Markov Random Fields(MRF) 모델은 영상 분할 및 복원 등에 주로 사용되는 확률적 영상모델이다. 본 논문에서는 MRF 모델을 3차원으로 확장하여 분할을 위한 선 필드 모델(Line Field Model)과 움직임 검출을 위한 움직임 필드 모델(Motion Field Model)을 도입하여 동영상 내에서 움직이는 물체의 형상과 움직임을 추정한다. 제안된 방법을 이용하여 한국어 수화 동작에서 손의 형상과 이동방향을 검출하였다. 그 결과 optical flow를 사용하는 방법에 비해서 이동 방향이 왜곡되는 것을 방지하여 보다 정확한 이동 방향을 검출할 수 있었다. 또한 영상 추출의 경우에 있어서도 형상의 윤곽면과 내부가 하나의 라벨(label)로 묶이기 때문에 보다 깨끗한 영상을 추출할 수 있었다.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.455-464
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• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.7-12
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• 2001

In this paper, an estimation method of hybrid feature was proposed to detect linear feature such as the road network from SAR(synthetics aperture radar) images that include speckle noise. First we considered the mean intensity ratio or the statistical properties of locality neighboring regions to detect linear feature of road. The responses of both methods are combined to detect the entire road network. The purpose of this paper is to extract the segments of road and to mutually connect them according to the identical intensity road from the locally detected fusing images. The algorithm proposed in this paper is to define MRF(markov random field) model of the priori knowledge on the roads and applied it to energy function of interacting density points, and to detect the road networks by optimizing the energy function.

• The KSFM Journal of Fluid Machinery
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• v.5 no.2 s.15
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• pp.29-35
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• 2002

The present study is concerned with the flow patterns induced by various impellers in a rectangular tank. Impellers are FBT (Flat blade turbine), PBT (Pitched blade turbine), Shroud turbine, Rushton turbine, and Helical ribbon turbine types. The solutions of flows in moving reference frames require the use of 'moving' cell zone. The moving zone approaches are based on MRF (Multiple reference frame), which is a steady-state approximation and sliding method, which is an unsteady-state approximation. Numerical results using two moving zone approaches we compared with experiments by Ranade & Joshi, which have done extensive LDA measurements of the flow generated by a standard six-bladed Rushton turbine in a cylindrical baffled vessel. In this paper, we simulated the flow patterns with above-mentioned moving zone approaches and impellers. Turbulence model used is RNG $k-{\epsilon}$ model. Sliding-mesh method is more effective than MRF for simulating the rectangular tank with inlet and outlet. RNG $k-{\epsilon}$ model strongly underestimates the velocity of experimental data and velocity by Chen & Kim's model, but it seems to be correctly predicted in overall distribution.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.37-44
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• 2006

In this paper, a new version of the ICM method(MICM, modified ICM) in which the contextual information is modelled by Markov random fields (MRF) is introduced. To extract the feature, a new local MRF model with a fitting block neighbourhood is proposed. This model selects contextual information not only from the relative intensity levels but also from the geometrically directional position of neighbouring cliques. Feature extraction depends on each block's contribution to the local variance. They discriminates it into several regions, for example context and background. Boundaries between these regions are also distinctive. The proposed algerian performs segmentation using directional block fitting procedure which confines merging to spatially adjacent elements and generates a partition such that pixels in unified cluster have a homogeneous intensity level. From experiment with ink rubbed copy images(Takbon, 拓本), this method is determined to be quite effective for feature identification. In particular, the new algorithm preserves the details of the images well without over- and under-smoothing problem occurring in general iterated conditional modes (ICM). And also, it may be noted that this method is applicable to the handwriting recognition.