• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2001년도 춘계 학술대회논문집
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• pp.127-133
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• 2001

In this paper, the preconditioned multistage time stepping methods which are popular multigrid smoothers is studied for the compressible flow calculations. Fourier analysis on the local time stepping and block-Jacobi preconditioned residual operators is performed using the linearized 2-D Navier-Stokes equations. It fumed out that block-Jacobi preconditioner has better performance in eigenvalue clustering. They are implemented in the 2-D compressible Euler and Wavier-Stokes calculations with multigrid methods to verify that the block-Jacobi preconditioned multistage time stepping shows better performance in convergence acceleration.

• 한국멀티미디어학회논문지
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• 제10권1호
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• pp.1-12
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• 2007

모바일 환경의 제한된 자원 하에서 멀티미디어 데이터를 이용하기 위해서는 XML로 표현되는 MPEG-7 문서의 효율적인 관리 방법이 필요하다. 이 때 XML 문서 클러스터링 방법들을 이용할 수 있겠으나 보다 효율성을 높이기 위해 MPEG-7 문서의 특성을 반영한 새로운 클러스터링 방법이 요구된다. 새로운 클러스터링은 모바일 환경에서 멀티미디어 검색시 질의 처리 속도가 향상되며 다양한 응용에 적합한 문서 저장이 가능하다. 본 논문에서는 대용량의 멀티미디어 데이터를 MPEG-7 문서로 효율적으로 관리하기 위해 MPEG-7 문서의 엘리먼트들 사이에 나타나는 의미 관련성을 이용해 저장할 수 있는 새로운 클러스터링 방법을 제안하고, 이를 기존 방법들과 비교하였다.

• 한국주거학회논문집
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• 제19권6호
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• pp.85-93
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• 2008

This study analyzes areas, traffic lines and characteristics of block of traditional villages in order to suggest how to build urban village in the way that can solve problems occurring in residential areas these days. The study showed the following results: 1) Traditional villages have definite boundary and entrance, and the community area for the villages is close to the entrance to encourage community activities of villagers. 2) With an access in the form of a blind alley branched from the main road, traditional villages form a small-sized clustering and encourage community activities in a natural way. 3) Formed of block with a pattern of net, blind alley or standing in a line on both sides, traditional villages help residents to form close relations between. These findings suggest that for building desirable urban villages, 1) they should have definite boundary, 2) size and location of community area should be determined in the way to activate community activities of residents, 3) roads inside the village should have branched form rather than standardized check pattern so that small-sized clustering could be formed along the branched inner roads, and 4) clustering in villages should be arranged in a line on both sides or in the form of a blind alley giving consideration to the length and width of roads. The roads should be also of a closed type so that residents could create strong bonds with their neighbors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.813-829
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• 2022

In multi-view subspace clustering, how to integrate the complementary information between perspectives to construct a unified representation is a critical problem. In the existing works, the unified representation is usually constructed in the original data space. However, when the data representation in each view is very diverse, the unified representation derived directly in the original data domain may lead to a huge information loss. To address this issue, different to the existing works, inspired by the latest revelation that the data across all perspectives have a very similar or close spectral block structure, we try to construct the unified representation in the spectral embedding domain. In this way, the complementary information across all perspectives can be fused into a unified representation with little information loss, since the spectral block structure from all views shares high consistency. In addition, to capture the global structure of data on each view with high accuracy and robustness both, we propose a novel low-rank approximation via the tight lower bound on the rank function. Finally, experimental results prove that, the proposed method has the effectiveness and robustness at the same time, compared with the state-of-art approaches.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.195-198
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.81-84
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• International Journal of Contents
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• 제9권1호
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• pp.6-10
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• 2013

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권7호
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• pp.911-921
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• 2004

지문영상으로부터 특징점을 정확하게 추출하는 것은 효과적인 지문인식 시스템의 구축에 매우 중요하다. 하지만 지문영상의 품질에 따라 특징점 추출의 정확도가 달라지기 때문에 지문인식 시스템에서의 영상 전처리 과정은 시스템의 성능에 크게 영향을 미친다. 본 논문에서는 지문영상으로부터 명암값의 평균 및 분산, 블록 방향성 차, 방향성 변화도, 융선과 골의 두께 비율 등의 5가지 특징을 추출하고 계층적 클러스터링 알고리즘으로 클러스터링하여 영상의 품질 특성을 분석한 후 습성(oily), 보통(neutral), 건성(dry)의 특성에 적합하게 영상을 개선하는 지식기반 전처리 방법을 제안한다. NIST DB 4와 인하대학교 데이타를 이용하여 실험한 결과, 클러스터링 기법이 영상의 특성을 제대로 구분함을 확인할 수 있었다. 또한 제안한 방법의 성능 평가를 위해 품질 지수와 블록 방향성 차이를 측정하여 일반적인 전처리 방법보다 지식기반 전처리 방법이 품질 지수와 블록 방향성 차이를 향상시킴을 확인할 수 있었다.

• Journal of information and communication convergence engineering
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• 제16권4호
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• pp.258-263
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• 2018

Color Doppler sonography is a useful tool for examining blood flow and related indices. However, it should be done by well-trained operator, that is, operator subjectivity exists. In this paper, we propose an automatic blood flow area extraction method from brachial artery that would be an essential building block of computer aided color Doppler analyzer. Specifically, our concern is to examine hypertension suspicious (prehypertension) patients who might develop their symptoms to established hypertension in the future. The proposed method uses fuzzy C-means clustering as quantization engine with careful seeding of the number of clusters from histogram analysis. The experiment verifies that the proposed method is feasible in that the successful extraction rates are 96% (successful in 48 out of 50 test cases) and demonstrated better performance than K-means based method in specificity and sensitivity analysis but the proposed method should be further refined as the retrospective analysis pointed out.

• 전자공학회논문지
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• 제51권2호
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• pp.124-132
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• 2014

본 논문은 퍼지 C-평균 분류기와 적응적 블록 분할을 사용한 역광 영역 검출과 공간 적응적 대비 확장을 사용한 역광 영역 개선 방법을 제안한다. 제안된 방법은 퍼지 이론에 의해 계산된 최적의 임계값을 기반으로 적응적 가변블록 분할을 사용하여 역광 영상을 어두운 역광 영역과 밝은 배경 영역으로 구분한다. 가변블록에 의한 블록화 현상을 없애기 위해 유도 필터(guided filter)를 사용하여 역광 영역을 객체 영역에 적합하게 세분화한다. 마지막으로 검출된 역광 영역은 공간 적응적으로 대비가 확장되어 조도를 개선한다. 제안된 방법은 최적의 임계값을 사용하여 영상을 분할하기 때문에 입력 영상에 따라 적응적으로 영역을 분할하고 저조도 영역을 개선하며, 사용자의 별도의 설정이 없이 입력 영상에 따라 자동적 역광 영상 개선이 가능하다. 실험 결과를 통해 제안된 방법이 기존 방법보다 역광 영역에 존재하는 피사체의 정보를 효과적으로 개선할 수 있으며, 복잡한 분할 방법을 사용하지 않고 빠르게 역광 영역을 검출할 수 있음을 보인다.