• Journal of Broadcast Engineering
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• v.4 no.1
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• pp.44-58
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• 1999

In this paper, a rate-distortion based image segmentation algorithm is presented using a recursive merging with region adjacency graph (RAG). In the method, the dissimilarity between a pair of adjacent regions is represented as a Lagrangian cost function considered in rate-distortion sense. Lagrangian multiplier is estimated in each merging step, a pair of adjacent regions whose cost is minimal is searched and then the pair of regions are merged into a new region. The merging step is recursively performed until some termination criterion is reached. The proposed method thus is suitable for region-based coding or segmented-based coding. Experiment results for 256x256 Lena show that segmented-based coding using the proposed method yields PSNR improvement of about 2.5 - 3.5 dB. 0.8 -1.0 dB. 0.3 -0.6 dB over mean-difference-based method. distortion-based method, and JPEG, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.35-44
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• 2009

This paper describes an application of domain decomposition method for parallel finite element analysis which is required to large scale 3D structural analysis. A parallel finite element method system which adopts a domain decomposition method is developed. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation method is introduced as a basic tool for element generation. Domain decomposition method using automatic mesh generation system holds great benefits for 3D analyses. Aa parallel numerical algorithm for the finite element analyses, domain decomposition method was combined with an iterative solver, i.e. the conjugate gradient(CG) method where a whole analysis domain is fictitiously divided into a number of subdomains without overlapping. Practical performance of the present system are demonstrated through several examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.72-75
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• 2010

본 논문에서는 열탄점소성 손상과 접촉 문제의 효율적인 해석을 위하여 적응성 영역/경계 분할법을 제안하였다. 적응성 영역/경계 분할법은 시간 증분 또는 반복 기법 단계에서 열탄점소성 손상과 같은 재료 비선형성을 감안하여 부영역을 재설정하며, 접촉에 따른 경계 비선형성은 경계면을 통하여 부영역으로부터 독립적으로 분할한다. 분할된 각각의 부영역과 경계면을 기준으로 유한요소 정식화를 수행하며, 공유면 및 접촉 공유면의 연속 구속 조건을 처리하기 위하여 벌칙 함수 기법을 적용하였다. 결과적으로 재료 및 경계 비선형성은 일부 부영역과 접촉 경계면에서 계산되는 유한요소 행렬에 국한된다. 수치 실험을 통하여 적응성 해석 알고리듬의 기본적인 특성과 효율성 향상에 대하여 분석하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.156-166
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• 2000

A rate-distortion based segmentation using recursive merging is presented, which considers texture as a homogeneity by adopting the procedure of a generalized texture approximation. The texture in a region is approximated by SA-DCT and a set of two uniform quantizers with fixed step sizes, one for DC and another for AC. Using the approximated texture, we calculated the rate-distortion based cost. The segmentation using recursive merging is performed by using the rate-distortion based cost. Experimental results for 256$\times$256 Lena show that the region-based coding using the proposed segmentation yields the PSNR improvements of 0.8~ 1.0 dB and 1.2~1.5 dB over that using the rate-distortion based segmentation with DC approximation only and JPEG, respectively.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.209-220
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• 2012

In this paper, we propose an adaptive pavement region detection method that is robust to changes of structural patterns in a natural scene. In order to segment out a pavement reliably, we propose two step approaches. We first detect the borderline of a pavement and separate out the candidate region of a pavement using VRays. The VRays are straight lines starting from a vanishing point. They split out the candidate region that includes the pavement in a radial shape. Once the candidate region is found, we next employ the adaptive multi-seed region growing(A-MSRG) method within the candidate region. The A-MSRG method segments out the pavement region very accurately by growing seed regions. The number of seed regions are to be determined adaptively depending on the encountered situation. We prove the effectiveness of our approach by comparing its performance against the performances of seed region growing(SRG) approach and multi-seed region growing(MSRG) approach in terms of the false detection rate.

• Proceedings of the Acoustical Society of Korea Conference
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• 1996.10a
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• pp.61-65
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• 1996

본 논문은, 공간영역에서 화상을 압축할 수 있는 Quad-tree 부호화법을 분석하고, 보다 화질 및 압축율을 개선하기 위하여 적응 불록분할 및 병합 알고리듭을 제안하엿다. 화상은 에지부분을 제외하고는 인접한 화소들간에 데이터의 용장도가 높으므로 이 영역을 하나의 대표값으로 설정하여 그 값과 그 블록의 위치좌표를 부호화할 수 있다. Quad-tree 분할은 초기의 병합을 제외하고 순차적으로 분할과정만 반복처리하지만 본 알고리듬에서는 단위블록(3$\times$3 호소) 의 평균잘류에너지(MRE)를 이용하여 블록의 분할과 병합을 반복처리한다. 시뮬레이션결과, 본 알고리듭은 압축율 1bit/pixel에서 기존의 Quad-tree 방법보다 PSNR에서 1.0dB의 개선이 있었으며, 화상의 블록화 현상도 전혀 나타나지 않았다.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.93-102
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• 2006

In this study an advanced domain decomposition method is suggested in order to construct surface models from very large amount of points. In this method the spatial domain of interest that is occupied by the input set of points is divided in repetitive manner. First, the space is divided into smaller domains where the problem can be solved independently. Then each subdomain is again divided into much smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together to obtain a solution of each subdomain using partition of unity function. Then the solutions of subdomains are merged together in order to construct whole surface model. The suggested methods are conceptually very simple and easy to implement. Since RDDM(Repetitive Domain Decomposition Method) is effective in the computation time and memory consumption, the present study is capable of providing a fast and accurate reconstructions of complex shapes from large amount of point data containing millions of points. The effectiveness and validity of the suggested methods are demonstrated by performing numerical experiments for the various types of point data.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.673-680
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• 2003

In this paper, we study the enhancement of VQ (Vector Quantization) design for text independent speaker recognition. In a concrete way, we present a non-iterative method which makes a vector quantization codebook and this method performs non-iterative learning so that the computational complexity is epochally reduced The proposed Classified Space VQ (CSVQ) design method for text Independent speaker recognition is generalized from Semi-noniterative VQ design method for text dependent speaker recognition. CSVQ contrasts with the existing desiEn method which uses the iterative learninE algorithm for every traininE speaker. The characteristics of a CSVQ design is as follows. First, the proposed method performs the non-iterative learning by using a Classified Space Codebook. Second, a quantization region of each speaker is equivalent for the quantization region of a Classified Space Codebook. And the quantization point of each speaker is the optimal point for the statistical distribution of each speaker in a quantization region of a Classified Space Codebook. Third, Classified Space Codebook (CSC) is constructed through Sample Vector Formation Method (CSVQ1, 2) and Hyper-Lattice Formation Method (CSVQ 3). In the numerical experiment, we use the 12th met-cepstrum feature vectors of 10 speakers and compare it with the existing method, changing the codebook size from 16 to 128 for each Classified Space Codebook. The recognition rate of the proposed method is 100% for CSVQ1, 2. It is equal to the recognition rate of the existing method. Therefore the proposed CSVQ design method is, reducing computational complexity and maintaining the recognition rate, new alternative proposal and CSVQ with CSC can be applied to a general purpose recognition.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.51-58
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• 2005

This paper proposes an efficient algorithm for extracting a tumor region from an breast ultrasound volume image by using rate-distortion (R-D) based seeded region growing. In the proposed algorithm the rate and the distortion represent the roughness of the contour and the dissimilarity of pixels in a region, respectively. Staring from an initial seed region set in each cutting plane of a volume, a pair of the seed region and one of adjacent regions whose R-D cost is minimal is searched and then they are merged into a new updated seed region. This procedure is recursively performed until the averaged R-D cost values per the number of contour pixels in the seed region becomes maxim. As a result, the final seed region has good pixel homogeneity and a much smooth contour. Finally, the tumor volume is extracted using the contours of the final seed regions in all the cutting planes. Experimental results show that the averaged error rate of the proposed method is shown to be below 4%.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.4
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• pp.369-378
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• 2010

The mixed finite element analysis is the most widely used method for saturated porous media. Generally, in this method, direct method and iterative method are proposed to obtain unknown variable, however, the iterative method is recommended because the method provide numerical stability and accuracy under the material properties for solid and fluid are different. In this paper, we introduce staggered method which has strong numerical stability, and FETI(Finite Element Tearing and Interconnecting) which is one of decomposition methods are applied into the method in order to obtain numerical efficiency. In which, Lagrange Multipliers and conjugated gradient method to solve decomposed domain are proposed, and then, the proposed method is verified numerical efficiency by point to point MPI(Message Passing Interface) library.