• Progress in Medical Physics
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• v.13 no.3
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• pp.169-175
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• 2002

The purpose of this study is to verify the usefulness of X-ray simulator which uses a visible light source for further study. We developed a small experimental equipment which is composed of three main components - source, localizer and detector. Cartesian coordinate was set in 3D space, and the position of target was assumed the origin of the coordinate. The light from the source passes directly through the target, and projection image is formed on the screen, which can be taken with the digital camera. Since projection images were acquired behind the screen, they were flipped over right and left. By examining the characters of visual light source and equipments, it could be concluded that developed system was useful for experimental purpose.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.739-742
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• 2001

동영상은 각 프레임 사이에 시간적으로나 공간적으로 많은 양의 정보가 중복되어 있다. 이러한 중복 정보를 줄이는 표현 방법들 중에 하나로, 동영상을 커다란 하나의 영상으로 정합하여 중복 정보를 줄이는 모자이크 기법이 있다. 두 개 이상의 영상을 정합하기 위해서는 영상간의 카메라 파라미터가 필요한데, 본 논문에서는 Mellin 변환을 사용하여 카메라 파라미터를 구하였다. 이때 3차원 공간모델은 직교 투사법을 사용하였으며, 영상의 움직임 모델로는 4개의 파라미터(평행이동, 확대/축소, 회전)를 사용한 어파인 움직임 모델을 사용하였다. 이렇게 구현된 파노라마 영상은 동영상에서 움직이는 물체를 검출하거나 추적하고, 동영상을 편집하는데 응용될 수 있다. 또한 본 연구의 최종 목적인 3D 영상의 배경을 구현하는 데 좀 더 사실적인 영상을 제공할 수 있다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.11
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• pp.1072-1078
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• 2008

An adaptive control algorithm for spacecraft rendezvous and docking in a Keplerian orbit is presented. The equations of relative motion of two spacecrafts expressed in a local-vertical-local-horizontal rectangular frame are converted to a general Hamiltonian form, then an adaptive control method developed for the uncertain Hamiltonian system is applied to the rendezvous and docking problem. A smooth projection algorithm is applied to keep the parameter estimates inside a singularity-free region, and a numerical example shows that the developed controller successfully deals with the unknown mass of the chaser spacecraft.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4A
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• pp.399-406
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• 2011

Adaptive beamformers, which utilize a priori information on the arrival angle of the desired signal. suppress interferences while maximizing their gains in the desired signal direction. However, if there exist errors in the direction information, they can suffer from severe performance degradation since the desired signal is treated as an interference. A robust adaptive beamforming method is presented which exploits the signal-blocking structure of the Duvall beamformer. The proposed method finds an interference signal space directly from correlations of received signals and then obtains a weight vector such that it is orthogonal to the space. Applying the weight vector to two sub arrays which consist of one less sensors than the original uniform lineal array (ULA), the beamformer efficiently estimates the arrival angle of the desired signal. Its computational complexity is lower than existing methods, which require matrix inversion or eigendecomposition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.883-887
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• 2009

This paper presents a statistical analysis of the MSE of adaptation for the MPDSAP (Maximally polyphase decomposed Subband Affine Projection) algorithm for the an autoregressive (AR) inputs with P order. In subband structure, the Affine Projection (AP) algorithm is transformed to the Normalized Least Mean Square (NLMS) algorithm by applying the polyphase decomposition and the noble identity to the adaptive filter. And also, AR input can be pre-whitened by subband filtering with the Orthonormal Analysis Filters(OAF). In the subband structure, the pre-whitening of the AR(P) inputs provides simple and valid approximations for a statistical analysis of the MSE behaviors for the SAP adaptive filter.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.50-55
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• 2002

The standard approach of image resampling is to fit the original image with continuous model and resample the function at a desired rate. We used the B-spline function as the continuous model because it oscillates less than the others. The main purpose of this paper is the derivation of a nonuniform optimal resampling algorithm. To derive it, needing approximation can be computed in three steps: 1) determining the I-spline coefficients by matrix inverse process, 2) obtaining the transformed-spline coefficients by the optimal resampling algorithm derived from the orthogonal projection theorem, 3) converting of the result back into the signal domain by indirect B-spline transformation. With these methods, we can use B-spline in the non-uniform resampling, which is proved to be a good kernel in uniform resampling, and can also verify the applicability from our experiments.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.117-126
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• 2008

Recent advances in medical imaging technologies have enabled the high-resolution data acquisition. Therefore visualization of such large data set on standard graphics hardware became a popular research theme. Among many visualization techniques, we focused on bricking method which divided the entire volume into smaller bricks and rendered them in order. Since it switches bet\W8n bricks on main memory and bricks on GPU memory on the fly, to achieve better performance, the number of these memory swapping conditions has to be minimized. And, because the original bricking algorithm was designed for regular volume data such as CT and MR, when applying the algorithm to ultrasound volume data which is based on the toroidal coordinate space, it revealed some performance degradation. In some areas near bricks' boundaries, an orthogonal viewing ray intersects the single brick twice, and it consequently makes a single brick memory to be uploaded onto GPU twice in a single frame. To avoid this redundancy, we divided the volume into bricks allowing overlapping between the bricks. In this paper, we suggest the formula to determine an appropriate size of these shared area between the bricks. Using our formula, we could minimize the memory bandwidth. and, at the same time, we could achieve better rendering performance.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.