• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.418-426
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• 2006

This paper proposes a robust and efficient segmentation method for a cardiac ultrasound image taken from a probe inserted into the heart in surgery. The method consists of three steps: initial boundary extraction, whole boundary modification using confidence competition, and local boundary modification using the rolling spoke method. Firstly, the initial boundary is extracted with threshold regions along the global spokes emitted from the center of an ultrasound probe. Secondly, high confidence boundary edges are detected along the global spokes by competing among initial boundary candidate and new candidates achieved by edge and appearance information. finally, the boundary is modified by rolling local spokes along concave regions that are difficult to extract using the global spokes. The proposed method produces promising segmentation results for the ultrasound cardiac images acquired during surgery.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.2
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• pp.108-115
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• 1992

이종재료의 접합면에 수직으로 존재하는 크랙에 대하여 경계요소 해석을 수행하여, 그 결과 실용가능한 수치 근사해을 얻을 수 있었다. 크랙을 정확히 모델링하기 위하여 크랙표면을 분리영역으로 하는 영역분할법을 채택하였으며, 해의 정확성을 향상시키기 위하여 등매개 2차요소로의 경계분할과 함께 크랙선단에서 표면력의 특이성을 나타내도록 하였다. 응력확대계수는 크랙표면상 절점의 상대변위를 이용하여 결정하였다. 또한 이종 재료내 크랙에 대하여 응력확대계수를 간단히 구할 수 있는 간편해석법을 제안하고 이의 적용 가능한 범위를 제 시하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.5
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• pp.475-482
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• 2010

In this paper, an efficient two-level parallel domain decomposition algorithm is suggested to solve large-DOF structural problems. Each subdomain is composed of the coarse problem and local problem. In the coarse problem, displacements at coarse nodes are computed by the iterative method that does not need to assemble a stiffness matrix for the whole coarse problem. Then displacements at local nodes are computed by Multi-Frontal Sparse Solver. A parallel version of PCG(Preconditioned Conjugate Gradient Method) is developed to solve the coarse problem iteratively, which minimizes the data communication amount between processors to increase the possible problem DOF size while maintaining the computational efficiency. The test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF structural problems.

• 전기의세계
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• v.39 no.3
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• pp.32-38
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• 1990

1960년대 후반 유한요소법인 전자장 수치해석에 응용되기 시작한 후 전기기기 특성해석, 성능예측 및 설계에 많은 도움을 주었다. 그동안 실제 모델에 응용된것은 거의가 2차원 문제에 국한되었다. 그러나, 최근 들어서는 각종 전기기기가 경량화, 소형화, 고효율화 됨에 따라 점차로 3차원 전자장 수치해석에 대한 요구가 급증하고 잇다. 앞서 언급한 바와 같이 유한요소법은 영역법의 일종으로 영역을 적절히 요소분할 하는데 어려움이 있다. 따라서 근래에 영역법의 문제점을 보완하기 위하여, 또한 영역법으 대용으로 경계법에 대한 연구가 점차로 증대되고 있다. 경계요소법은 주어진 지배방정식에 대한 Green 함수를 반드시 알아야만 하는 단점을 갖고 있으나 근래에 들어서는 광범위한 분야에 걸쳐 Grem함수가 이미 발전되어 있기 때문에 실제 응용에는 별 문제가 없으리라 생각된다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.12
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• pp.102-107
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• 2009

As technology gets developed, medical equipments are also modernized and leading-edge systems, such as PACS become popular. Many scientists noticed importance of medical image processing technology. Technique of region segmentation is the first step of digital medical image processing. Segmentation technique helps doctors to find out abnormal symptoms early, such as tumors, edema, and necrotic tissue, and helps to diagnoses correctly. Segmentation of white matter, gray matter and CSF of a brain image is very crucial part. However, the segmentation is not easy due to ambiguous boundaries and inhomogeneous physical characteristics. The rate of incorrect segmentation is high because of these difficulties. Fuzzy-based segmentation algorithms are robust to even ambiguous boundaries. In this paper a modified Fuzzy-based segmentation algorithm is proposed to handle the noise of MR scanners. A proposed algorithm requires minimal computations of mean and variance of neighbor pixels to adjust a new neighbor list. With the addition of minimal compuation, the modified FCM(mFCM) lowers the rate of incorrect clustering below 30% approximately compared the traditional FCM.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.756-759
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• 2011

일반적으로 컴퓨터를 이용한 수치 해석에는 격자 수치 해석 방법인 유한요소법 또는 유한차분법이 주로 사용되어 왔다. 그러나 이러한 방법들은 해석하고자 하는 영역을 요소나 격자 등으로 분할해야 하기 때문에 복잡한 현상들을 다루는 데 어려움을 갖게 된다. 이를 극복하기 위해 개발된 방법이 무요소법(Meshfree Method)이며 본 논문에서는 다양한 무요소법들 중 SPH(Smoothed Particle Hydrodynamics)가 고려되어진다. SPH는 라그랑지안 수치 근사 기법을 사용하는 입자법(Particle Method)으로 SPH를 정확하게 실행하기 위해서는 적절한 경계 처리법이 요구된다. 그러나 기존의 경계 처리법은 유체 입자의 침투현상 및 커널(Kernel) 끊김 현상이 발생하기 때문에 적합하지 않다. 따라서 지금까지 SPH의 경계 처리법을 향상시키기 위해 다양한 접근법들이 제안되었으며 본 논문에서는 이러한 접근법들 중 정반사(Specular Reflection), 재회복(Bounce-back), 재도입(Reintroduce) 방법 및 경계 반발력(Repulsive Force)과 가상 입자(Ghost Particle)의 적용이 분석되고 현상 접목을 통해 적절한 경계 처리법이 제안되어진다.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.15-22
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• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.38-46
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• 2004

Image segmentation is the task which partitions the image into meaningful regions and considered to be one of the most important steps in computer vision and image processing. Image segmentation is also widely used in object-based video compression such as MPEG-4 to extract out the object regions from the given frame. Watershed algorithm is frequently used to obtain the more accurate region boundaries. But, it is well known that the watershed algorithm is extremely sensitive to gradient noise and usually results in oversegmentation. To solve such a problem, we propose an image segmentation method which is robust to noise by using stabilized inverse diffusion equation (SIDE) and is more efficient in segmentation by employing multiresolution approach. In this paper, we apply both the region projection method using labels of adjacent regions and the region merging method based on region adjacency graph (RAG). Experimental results on noisy image show that the oversegmenation is reduced and segmentation efficiency is increased.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.9-16
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• 2006

This Paper proposes an adaptive error diffusioThis paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, and the MGD values are filled within a local window to merge the potential text segments. Isolated segments are then eliminated in the non-text region filtering process. After the left segmentation, a conventional error diffusion method is applied to the background, while the edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, the gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) prevents the printing of successive dots around the text region boundaries. The error diffusion algorithm with edge enhancement is extended to halftone color images to sharpen the tort regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, the additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. By using the proposed algorithm, the text of a scanned image is sharper than that with a conventional error diffusion without changing background.