• 제목/요약/키워드: Level set methods

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최소자승법과 Level-set 방법을 이용한 3차원 슬로싱 유동의 수치해석 (Numerical analysis of three-dimensional sloshing flow using least-square and level-set method)

  • 최형권
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회B
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    • pp.2401-2405
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    • 2008
  • In the present study, a three-dimensional least square/level set based two-phase flow code was developed for the simulation of three-dimensional sloshing problems using finite element discretization. The present method can be utilized for the analysis of a free surface flow problem in a complex geometry due to the feature of FEM. Since the finite element method is employed for the spatial discretization of governing equations, an unstructured mesh can be naturally adopted for the level set simulation of a free surface flow without an additional load for the code development except that solution methods of the hyperbolic type redistancing and advection equations of the level set function should be devised in order to give a bounded solution on the unstructured mesh. From the numerical experiments of the present study, it is shown that the proposed method is both robust and accurate for the simulation of three-dimensional sloshing problems.

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A MULTIPHASE LEVEL SET FRAMEWORK FOR IMAGE SEGMENTATION USING GLOBAL AND LOCAL IMAGE FITTING ENERGY

  • TERBISH, DULTUYA;ADIYA, ENKHBOLOR;KANG, MYUNGJOO
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제21권2호
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    • pp.63-73
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    • 2017
  • Segmenting the image into multiple regions is at the core of image processing. Many segmentation formulations of an images with multiple regions have been suggested over the years. We consider segmentation algorithm based on the multi-phase level set method in this work. Proposed method gives the best result upon other methods found in the references. Moreover it can segment images with intensity inhomogeneity and have multiple junction. We extend our method (GLIF) in [T. Dultuya, and M. Kang, Segmentation with shape prior using global and local image fitting energy, J.KSIAM Vol.18, No.3, 225-244, 2014.] using a multiphase level set formulation to segment images with multiple regions and junction. We test our method on different images and compare the method to other existing methods.

다중 해상도 레벨 세트 방식을 이용한 기하 활성 모델 (A Geometric Active Contour Model Using Multi Resolution Level Set Methods)

  • 김성곤;김두영
    • 한국정보처리학회논문지
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    • 제6권10호
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    • pp.2809-2815
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    • 1999
  • Level set, and active contour(snakes) models are extensively used for image segmentation or shape extraction in computer vision. Snakes utilize the energy minimization concepts, and level set is based on the curve evolution in order to extract contours from image data. In general, these two models have their own drawbacks. For instance, snake acts pooly unless it is placed close to the wanted shape boundary, and it has difficult problem when image has multiple objects to be extracted. But, level set method is free of initial curve position problem, and has ability to handle topology of multiple objects. Nevertheless, level set method requires much more calculation time compared to snake model. In this paper, we use good points of two described models and also apply multi resolution algorithm in order to speed up the process without decreasing the performance of the shape extraction.

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PCB조립 라인의 준비 시간 단축 및 재공품 감소를 위한 스케줄링 전략 (A Scheduling Strategy for Reducing Set-up Time and Work-In-Process in PCB Assembly Line)

  • 이영해;김덕한;전성진
    • 한국경영과학회지
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    • 제22권1호
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    • pp.25-49
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    • 1997
  • Printed circuit board (PCB) assembly line configuration is characterized by very long set-up times and high work in process (WIP) inventory level. The scheduling method can significantly reduce the set-up times and WIP inventory level. Greedy sequence dependent scheduling (GSDS) method is proposed based on the current methods. The proposed method is compared with the current method in terms of three performance measures: line throughput, average WIP inventory level, and implementation complexity.

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스네이크와 레벨 셋 방법을 결합한 개체 윤곽 추출 알고리즘 (Object Contour Extraction Algorithm Combined Snake with Level Set)

  • 황재용;오응군;장종환
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제3권5호
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    • pp.195-200
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    • 2014
  • 능동 개체 윤곽 추출의 대표적인 방법은 스네이크(Snake)와 레벨 셋(Level Set) 기술이다. 일반적으로 스네이크는 속도는 빠르나 개체 위상을 처리하는 데 제약이 있다. 그러나 레벨 셋은 속도는 느리지만 개체 위상에 관계없이 잘 처리할 수 있는 장점이 있다. 본 논문에서는 빠르고 복잡한 위상을 처리하기 위해 두 방법의 장점을 이용한 알고리즘을 제안한다. 알고리즘은 2단계로 구성된다. 첫 번째 단계는 스네이크를 사용하여 빠르게 개체의 대략적인 윤곽을 추출한 후 레벨 셋을 두 번째 적용하여 복잡한 개체 윤곽을 정확하게 추출한다. 제안한 알고리즘은 다양한 위상을 갖는 5개의 이진영상 및 2개의 자연영상에 적용하여 속도 및 윤곽 추출이 개선된 것을 보여 준다.

디지털 CMOS 회로의 Multi-Level Test를 위한 범용 Test Set 생성 (Universal Test Set Generation for Multi-Level Test of Digital CMOS Circuits)

  • Dong Wook Kim
    • 전자공학회논문지A
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    • 제30A권2호
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    • pp.63-75
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    • 1993
  • As the CMOS technology becomes the most dominant circuit realization method, the cost problem for the test which includes both the transistor-level FET stuck-on and stuck-off faults and the gatelevel stuck-at faults becomes more and more serious. In accordance, this paper proposes a test set and its generation algorithm, which handles both the transistor-level faults and the gate-level faults, thus can unify the test steps during the IC design and fabrication procedure. This algorithm uses only the logic equation of the given logic function as the input resource without referring the transistor of gate circuit. Also, the resultant test set from this algorithm can improve in both the complexity of the generation algorithm and the time to apply the test as well as unify the test steps in comparing the existing methods.

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A Level Set Method to Image Segmentation Based on Local Direction Gradient

  • Peng, Yanjun;Ma, Yingran
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권4호
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    • pp.1760-1778
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    • 2018
  • For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

Contrast-enhanced Bias-corrected Distance-regularized Level Set Method Applied to Hippocampus Segmentation

  • Selma, Tisa;Madusanka, Nuwan;Kim, Tae-Hyung;Kim, Young-Hoon;Mun, Chi-Woong;Choi, Heung-Kook
    • 한국멀티미디어학회논문지
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    • 제19권8호
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    • pp.1236-1247
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    • 2016
  • Recently, the level set has become a popular method in many research fields. The main reason is that it can be modified into many variants. One such case is our proposed method. We describe a contrast-enhancement method to segment the hippocampal region from the background. However, the hippocampus region has quite similar intensities to the neighboring pixel intensities. In addition, to handle the inhomogeneous intensities of the hippocampus, we used a bias correction before hippocampal segmentation. Thus, we developed a contrast-enhanced bias-corrected distance-regularized level set (CBDLS) to segment the hippocampus in magnetic resonance imaging (MRI). It shows better performance than the distance-regularized level set evolution (DLS) and bias-corrected distance-regularized level set (BDLS) methods in 33 MRI images of one normal patient. Segmentation after contrast enhancement and bias correction can be done more accurately than segmentation while not using a bias-correction method and without contrast enhancement.

Segmentation of Neuronal Axons in Brainbow Images

  • Kim, Tae-Yun;Kang, Mi-Sun;Kim, Myoung-Hee;Choi, Heung-Kook
    • 한국멀티미디어학회논문지
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    • 제15권12호
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    • pp.1417-1429
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    • 2012
  • In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

유한요소법을 이용한 level set 공식화의 해석 (FINITE ELEMENT ANALYSIS OF LEVEL SET FORMULATION)

  • 최형권
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2009년 추계학술대회논문집
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    • pp.223-227
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    • 2009
  • In the present study, a least square weighted residual method and Taylor-Galerkin method were formulated and tested for the discretization of the two hyperbolic type equations of level set method; advection and reinitialization equations. The two approaches were compared by solving a time reversed vortex flow and three-dimensional broken dam flow by employing a four-step splitting finite element method for the solution of the incompressible Navier-Stokes equations. From the numerical experiments, it was shown that the least square method is more accurate and conservative than Taylor-Galerkin method and both methods are approximately first order accurate when both advection and reinitialization phase are involved in the evolution of free surface.

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