• Journal of the Society of Naval Architects of Korea
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• v.41 no.2
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• pp.79-89
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• 2004

The viscous free surface flow around KRISO container ship (KCS) is computed using the finite volume based multi block RANS code, WAVIS developed at KRISO. The free surface is captured with the Level-Set method and the realizable k-$\varepsilon$ model is employed for turbulence closure. The computations are carried out at model scale. For accurate free surface solution and its stable convergence the computations are performed with a suitable grid refinement around the free surface by applying an implicit discretization method based on a finite volume method to the Level-Set formulation. In all computational cases the numerical results agree well with experimental measurements.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1142-1153
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• 2010

Conjunctival injection is the initial symptom of various eye diseases such as conjunctivitis, keratitis, or uveitis. The quantification of conjunctival injection may help the diagnosis and follow-up evaluation of various eye diseases. The size of the sclera is an important factor for the quantification of conjunctival injection. However, previous manual segmentation is time-consuming.Automatic segmentation is needed to extract the objective region of interest. This paper proposed a method based on the level set algorithm to segment the sclera from an anterior eye image. The initial model of the level set algorithm is calculated using the Lab color space, k-means algorithm and the geometric information. The level set algorithm was applied to the images in which the valley between the eyeball and skin was enhanced using the hessian analysis. This algorithm was tested with 52 images of the anterior eye segment. Results showed that the proposed method performs better than those with the level set algorithm using an arbitrary circle, or the region growing algorithm with color information. The proposed method for the segmentation of sclera may become an important component for the objective measurement of the conjunctival injection.

• Journal of Korea Multimedia Society
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• v.15 no.12
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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.

• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.218-222
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• 2009

A level-set (LS) method is presented for computation of boiling phenomena which involve liquid-vapor interfaces that evolve, merge and break up in time, the flow and temperature fields influenced by the interfacial motion, and the microlayer that forms between the solid and the vapor phase near the wall. The LS formulation for tracking the phase interfaces is modified to include the effects of phase change on the liquid-vapor interface and contact angle on the liquid-vapor-solid interline. The LS method can calculate an interface curvature accurately by using a smooth distance function. Also, it is straightforward to implement for two-phase flows in complex geometries. The numerical method is applied for analysis of nucleate boiling on a horizontal surface and film boiling on a horizontal cylinder.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.299-306
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• 2006

Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The 'Hamilton-Jacobi (H-J)' equation and computationally robust numerical technique of 'up-wind scheme' lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H -J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes is not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.6-9
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• 2011

In this study, the two-phase incompressible flow in two-dimensional channel considering the effect of surface tension is simulated using an improved level-set method. Quadratic element is used for solving the continuity and Navier-Stokes equations to avoid using an additional pressure equation, and Crank-Nicholson scheme and linear element are used for solving the advection equation of the level set function. Direct approach method using geometric information is implemented instead of the hyperbolic-type partial differential equation for the reinitializing the level set function. The benchmark test case considers various arrays of defomable droplets under different flow conditions in straight channel. The deformation and migration of the droplets are computed and the results are compared very well with the existing studies.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.116-121
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• 2006

Numerical simulations for dendritic growth of crystals are conducted in this study by the level set method. The effect of order of difference is tested for reinitialization error in simple problems and authors founded in case of 1st order of difference that very fine grids have to be used to minimize the error and higher order of difference is desirable to minimize the reinitialization error The 2nd and 4th order Runge-Kutta scheme in time and 3rd and 5th order of WENO schemes with Godunov scheme are applied for space discretization. Numerical results are compared with the analytical theory, phase-field method and other researcher's level set method.

• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.827-833
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• 2015

In this paper, we have compared three level set-based active contour (LSAC) methods on inhomogeneous MR image segmentation which is known as an important role of brain diseases to diagnosis and treatment in early. MR image is often occurred a problem with similar intensities and weak boundaries which have been causing many segmentation methods. However, LSAC method could be able to segment the targets such as the level set based on the local image fitting energy, the local binary fitting energy, and local Gaussian distribution fitting energy. Our implemented and tested the subcortical image segmentations were the corpus callosum and hippocampus and finally demonstrated their effectiveness. Consequently, the level set based on local Gaussian distribution fitting energy has obtained the best model to accurate and robust for the subcortical image segmentation.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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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.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.3
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• pp.293-298
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• 2013