• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.45-52
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• 2016

This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1750-1751
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• 2007

이동하고자 하는 경로에 자석 마커를 설치하고 마커의 자계를 인식하여 경로를 추종하는 이동 로봇의 경로 제어시스템이다. 자석마커 간격 확장과 여러 환경에 따른 자계를 분석하기 위해 자동 자계 측정 장치를 제작하였고, 이를 이용한 실측을 통하여 지자기 제거를 확인하였다. 지자기가 제거된 마커 자기장 값의 정규화와 선형화를 통하여 이동 경로 상에서 위치 인식이 수월하도록 하였으며, 인식된 경로 정보로 이동 로봇의 경로 제어가 가능하도록 하였다.

• Geophysics and Geophysical Exploration
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• v.15 no.2
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• pp.66-74
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• 2012

This paper presents development of a three-dimensional marine controlled-source electromagnetic (mCSEM) modeling algorithm and its application to a salt and reservoir model to examine detectability of mCSEM for a reservoir under complex subsurface structures. The algorithm is based on the finite difference method, and employs the secondary field formulation for an accurate and fast calculation of modeling responses. The algorithm is verified for a two-layer model by comparing solutions not only with analytic solutions but also with those from other 3D modeling algorithm. We calculate and analyze electric and magnetic fields and their normalized responses for a salt and reservoir model due to three sources located at boundaries between a salt, a reservoir, and background. Numbers and positions of resistive anomalies are informed by normalized responses for three sources, and types of resistive anomalies can be informed when there is a priori information about a salt by seismic exploration.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.760-762
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• 1999

본 논문에서는 기존의 적응필터인 LMS(Least Mean Square)와 RLS(Recursive Least Square)의 수렴속도의 향상과 안정성을 개선하기 위한 방안을 제안하였다. 제안된 알고리즘은 기존의 시간영역 LMS 알고리즘보다 상당히 빠른 수렴속도를 보일 수 있도록 설계하였다. RLS 알고리즘는 역행렬연산으로 인한 연산량이 많고 자기상관행렬이 positive definite 특성을 잃어버릴 경우 시스템이 수치적으로 불안정하게 되어 발산하는 단점이 있다. 이런한 단점을 보완하기 위해 제안된 알고리즘을 사용하였다. 기존의 알고리즘은 전력 정규화 과정에서 입력신호의 변환이 백색화가 완전히 이루어지지 않게 되어 자기상관행렬이 순수한 대각행렬이 되지 않는 단점을 지니고 있으나, 본 연구에서는 이러한 대각화 과정에서 좀더 많은 정보를 포함하도록 설계하였다. 아울러 제안된 알고리즘을 적응 등화기에 적용하여 수렴속도가 개선됨을 검증하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.562-564
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• 2002

본 논문에서는 자기상관함수의 국소적 특징을 사용하여 에지 특징을 추출한 후, 이를 이용해 유사이미지를 검색하는 방법을 제시한다. 자기상관함수의 국소적 특징을 이용하여 이미지를 검색할 경우 크기, 밝기, 색상등과 같은 이미지 요소가 서로 다를 경우에도 영향을 받지 않고 에지 특징정보를 추출해 낼 수 있다. 이는 얻어진 에지 특징을 이미지 크기와 고차 국소 자기상관함수의 변위에 의해 변하지 않도록 정규화를 하고, 동일 이미지에 대해 밝기가 조금 달라지면 검색효율이 떨어지는 점을 해결하기 위해 거리척도로서 방향여현거리(direction cosine distance)를 이용함으로써 가능하다. 이렇게 추출된 특징벡터를 자기조직화 맵에 의하여 클러스터링하고, 유사이미지 검색의 효율성을 비교해본 결과, 본 논문에서 제시한 방법을 사용하여 검색한 경우 재현율이 기존의 방법에 비해서 비교적 높은 수치를 나타냈다.

• The Korean Journal of Archival Studies
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• no.64
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• pp.5-25
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• 2020

The archives should not document the absence of labor records, but document the traces of workers' lives. In other words, it is the responsibility of the archive to reproduce the acts and sufferings of contingent workers with records, and to reveal the oppressive structure of capitalism based on them. Records representing the lives of contingent workers, such as labor manuals, should be at the core of records that symbolize the present, and archives should be documented. The archives should discard the illusion of neutrality.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.20-24
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• 1994

A new speech recognition model, DLSMM(Dynamically Localized Self-organizing Map Model) and its effective training algorithm are proposed in this paper. In DLSMM, temporal and spatial distortions of speech are efficiently normalized by dynamic programming technique and localized self-organizing maps, respectively. Experiments on Korean digits recognition have been carried out. DLSMM has smaller Experiments on Korean digits recognition have been carried out. DLSMM has smaller connections than predictive neural network models, but it has scored a little high recognition rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.164-167
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• 2007

스테레오 정합을 하기 위해서 먼저 두 이미지의 자기를 정규화 하였고, 밝기가 정규화 된 영상을 이용하여 Canny방식으로 Edge를 검출한 후 에지 적응형 스테레오 정합 방식으로 두 영상을 정합하여 변이도 영상들을 얻었다. 그 중 Canny Edge 방식이 다른 Edge 검출 방식보다 선명한 영상을 추출했다. Canny Edge 방식으로 획득한 스테레오영상을 중위수 필터를 사용하여 잡음을 제거한 후, 필터링 전 후의 영상을 PSNR(Peak Signal to Noise Ratio)로 비교하여 본 결과 개선된 영상을 획득 하였다.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.2
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• pp.101-111
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• 2008

Strain imaging in a medical ultrasound imaging system can differentiate the cancer or tumor in a lesion that is stiffer than the surrounding tissue. In this paper, a strain imaging technique using quasistatic compression is implemented that estimates the displacement between pre- and postcompression ultrasound echoes and obtains strain by differentiating it in the spatial direction. Displacements are computed from the phase difference of complex baseband signals obtained using their autocorrelation, and errors associated with converting the phase difference into time or distance are compensated for by taking into the center frequency variation. Also, to reduce the effect of operator's hand motion, the displacements of all scanlines are normalized with the result that satisfactory strain image quality has been obtained. These techniques have been incorporated into implementing a medical ultrasound strain imaging system that operates in real time.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1698-1705
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• 2010

In this paper, we propose a fast liver segmentation method from magnetic resonance(MR) images. Our method efficiently divides a MR image into a set of discrete objects, and boundaries based on the normalized gradient magnitude information. Then, the objects belonging to the liver are detected by using 2D seeded region growing with seed points, which are extracted from the segmented liver region of the slice immediately above or below the current slice. Finally, rolling ball algorithm, and connected component analysis minimizes false positive error near the liver boundaries. Our method was validated by twenty data sets and the results were compared with the manually segmented result. The average volumetric overlap error was 5.2%, and average absolute volumetric measurement error was 1.9%. The average processing time for segmenting one data set was about three seconds. Our method could be used for computer-aided liver diagnosis, which requires a fast and accurate segmentation of liver.