• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1127-1136
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• 1995

In this paper, a morphological shape decomposition method is proposed for the purpose of pattern recognition and image compression. In the method, a structuring element that geometrical characteristics is more similar to the shape function is preselected. The shape is decomposed into the primitive elements corresponding to the structuring element. A gray scale image also is transformed into 8 bit plane images for the hierarchical reconstruction required in image communication systems. The shape in each bitplane is decomposed to the proposed method. Through the experiment. it is proved that the description error is reduced and the coding efficiency is improved.

• Journal of the Ergonomics Society of Korea
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• v.13 no.2
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• pp.33-41
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• 1994

The paper presents a new scheme and a support system for the analysis sof hyman errors in nuclear power plants based on a cognitive model. We discusse the problems identified in current managerial analysis, and propose a new approach that frames the description of human activities according to a human decision making modle, so that it could provide a better reconstruction of a sequence of event suspected of involving human errors. This sophistcated approach becomes practical for the field application with the support of a computerized aiding system. The model-based event re-construction method is expected to enable the analysts to produce more informative reports, which in turn heop to derive appropriate counter- measures to reduce the possibility of the analyzed human errors.

• Journal of the Optical Society of Korea
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• v.13 no.2
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• pp.173-177
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• 2009

Digital holographic microscopy allows optical path difference measurement. Optical path difference depends on the both refractive index and morphology of sample. We developed a dual-wavelength in-line digital holographic microscope that can measure simultaneously the refractive index and morphology of a sample, providing highly precise three-dimensional information. Here we propose theoretical and experimental methods for dual-wavelength in-line digital holographic microscopy. The measured data were reasonable, although there was data error. By improving the experimental method, we could measure the refractive index more precisely and obtain more accurate three-dimensional information on samples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.224-241
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• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1863-1866
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• 2003

In this study, respiratory motion is modeled by a 2-Dimensional linear expanding-shrinking movement. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimated, a reconstruction algorithm based on superposition method was used to removed the MRI artifact. For the purpose of estimating unknown motion parameters, we applied the spectrum shift method to find the respiratory fluctuation function, the x directional expansion coefficient and its center, and also we used the minimum energy method to find the y directional expansion coefficient and its center. The effectiveness of this presented method is shown by Computer simulations.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.35-37
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• 2007

Super resolution using stochastic approach which based on the Bayesian approach is to easy modeling for a priori knowledge. Generally, the Bayesian estimation is used when the posterior probability density function of the original image can be established. In this paper, we introduced the improved MAP algorithm based on Bayesian which is stochastic approach in spatial domain. And we presented the observation model between the HR images and LR images applied with MAP reconstruction method which is one of the major in the SR grid construction. Its test results, which are operation speed, chip size and output high resolution image Quality. are significantly improved.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.19-25
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• 1998

발란싱 축소모델의 상태변수는 플랜트의 상태변수에 대한 정보를 주지 못한다. 발란싱 축소모델을 좌표 변환하여 얻은 상태유지 축소모델은 그 축소오차가 발란싱 축소모델의 축소오차와 같음을 증명하였다. 상태축소오차를 정의하였고, 이 오차를 구하는 방법을 제시하였는데, 이 오차는 축소모델의 차수가 정해지면 불변임을 증명하였다. 상태유지 축소모델의 상태변수는 그 상태축소오차가 작은 경우 원 시스템의 상태변수를 근사하는 장점이 있다. 상태유지 축소모델을 저차원제어기 설계에 적용하여 저차원 상태변수가 플랜트의 상태변수를 근사하는 예를 보여주었다.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.137-139
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• 2008

This study presents an approach to reconstruct high-resolution imagery for multispectral imagery of low-resolution using panchromatic imagery of high-resolution. The proposed scheme reconstructs a high-resolution image which agrees with original spectral values. It uses a linear model of high-and low- resolution images and consists of two stages. In this study, an 1m RGB image was generated from 4m IKONOS multispectral data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.10a
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• pp.13-18
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• 2004

In this study, a new method is proposed generating 3D wire-frames of building using the lowest level topology, points, which are input by human operators. Through the procedure, it is possible to make prediction occlusion points and generate the topology automatically among points, lines, surfaces from buildings. In order to adjust the error of initial values which are input manually, the least squares adjustment for model-image fitting is carried out using the edge information of aerial imagery. And also, model fitting procedure is done making all surfaces plane of buildings by the least squares adjustment. As a result of those procedure, 3D building models are refined similar to real figures of buildings.