• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.506-508
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• 1999

본 논문에서 제안하는 계층적인 형태의 deformable model을 이용하면 기존의 deformable model 방법이 가지고 있던 여러 문제점을 해결할 수 있다. 특히 가장 큰 문제중의 하나인 초기위치를 찾는 문제나 적용시간이 오래 걸린다는 단점을 상당부분 해결할 수 있다. 또한 계층적인 형태를 사용하면 최종적으로 찾고자 하는 문체가 증가될수록 더 많은 시간상/공간상의 이익을 볼 수 있게 된다. 본 논문에서는 이처럼 계층적인 형태로 deformable model을 구성하는 방법과 계층적 deformable model을 영상에 적용하는 방법, 그리고 그 방법에 대한 공간적/시간적 복잡도 분석을 통해 그 효율성을 알아보았다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2163-2170
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• 2009

We present an automated, energy minimized-based method for Lung parenchyma segmenting Chest Computed Tomography(CT) datasets. Deformable model is used for energy minimized segmentation. Quantitative knowledge including expected volume, shape of Chest CT provides more feature constrain to diagnosis or surgery operation planning. Segmentation subdivides an lung image into its consistent regions or objects. Depends on energy-minimizing, the level detail image of subdivision is carried. Segmentation should stop when the objects or region of interest in an application have been detected. The deformable model that has attracted the most attention to date is popularly known as snakes. Snakes or deformable contour models represent a special case of the general multidimensional deformable model theory. This is used extensively in computer vision and image processing applications, particularly to locate object boundaries, in the mean time a new type of external force for deformable models, called gradient vector flow(GVF) was introduced by Xu. Our proposed algorithm of deformable model is new external energy of GVF for exact segmentation. In this paper, Clinical material for experiments shows better results of proposal algorithm in Lung parenchyma segmentation on Chest CT.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.183-188
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• 2007

In this paper, we propose a 2D-FE model in single impact with combined physical factors to obtain a unique residual stress by shot peening. Applied physical parameters include elastic-plastic deformation of shot ball, material damping coefficients, strain rate, dynamic friction coefficients. Single impact FE model consists of 2D axisymmetric elements. The FE model with combined factors showed converged and unique distributions of surface stress, maximum compressive residual stress and deformation depth. Further, in contrast to the FE models with rigid shot and elastic deformable shot, FE model with plastic deformable shot produces residual stresses very close to experimental solutions by X-ray diffraction. We therefore validated the 2D FE model with combined peeing factors and plastic deformable shot. This FE model will be a base of the 3D FE model for residual stresses by multi-impact shot peening.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.19-24
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• 2008

This paper presents a physically-based haptic rendering algorithm for a deformable object based on visual information about the intervention between a tool and a real object in a remote place. The physically-based model of a deformable object is created from the mechanical properties of the object and the captured image obtained with a CCD camera. When a slave system exerts manipulation tasks on a deformable object, the reaction force for haptic rendering is computed using boundary element method. Snakes algorithm is used to obtain the geometry information of a deformable object. The proposed haptic rendering algorithm can provide haptic feedback to a user without using a force transducer in a teleoperation system.

• Korean Journal of Computational Design and Engineering
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• v.15 no.2
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• pp.136-143
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• 2010

Realistic Modeling is to maximize the reality of the environment in which perception is made by virtual environment or remote control using two or more senses of human. Especially, the field of haptic rendering, which provides reality through interaction of visual and tactual sense in realistic model, has brought attention. Haptic rendering calculates the force caused by model deformation during interaction with a virtual model and returns it to the user. Deformable model in the haptic rendering has more complexity than a rigid body because the deformation is calculated inside as well as the outside the model. For this model, Gibson suggested the 3D ChainMail algorithm using volumetric data. However, in case of the deformable model with non-homogeneous materials, there were some discordances between visual and tactual sense information when calculating the force-feedback in real time. Therefore, we propose an algorithm for the Volume Haptic Rendering of non-homogeneous deformable object that reflects the force-feedback consistently in real time, depending on visual information (the amount of deformation), without any post-processing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.768-773
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• 2004

Developed in this paper a mass-spring engine to represent and manipulate deformable objects. The deformable object model is a basic technology in the ‘Tangible Space Initiative’. The mass-spring model consists of structural, shear and bending springs. Various forces like external, friction, gravity, spring, and damping forces are considered and collision with planes and spheres are treated. When a sphere collide mass-spring model, mass-spring engine calculates external force to interface mass-spring model. A prototype system is implemented in C on an MS windows machine.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.373-380
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• 2006

Accurate and fast haptic simulations of deformable objects are desired in many applications such as medical virtual reality. In haptic interactions with a coarse model, the number of nodes near the haptic interaction region is too few to generate detailed deformation. Thus, local refinement techniques need to be developed. Many approaches have employed purely geometric subdivision schemes, but they are not proper in describing the deformation behavior of deformable objects. This paper presents a continuum mechanics-based finite element adaptive method to perform haptic interaction 'with a deformable object. This method superimposes a local fine mesh upon a global coarse model, which consists of the entire deformable object. The local mesh and the global mesh are coupled by the s-version finite element method (s-FEM), which is generally used to enhance accurate solutions near the target points even more. The s-FEM can demonstrate a reliable deformation to users in real-time.

• Journal of the Korea Computer Graphics Society
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• v.6 no.1
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• pp.19-27
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• 2000

This paper proposes a non-self-intersecting multiresolution deformable model to extract and reconstruct three-dimensional boundaries of objects from volumetric data. Deformable models offer an attractive method for extracting and reconstructing the boundary surfaces. However, convensional deformable models have three limitations- sensitivity to model initialization, difficulties in dealing with severe object concavities, and model self-intersections. We address the initialization problem by multiresolution model representation, which progressively refines the deformable model based on multiresolution volumetric data in order to extract the boundaries of the objects in a coarse-to-fine fashion. The concavity problem is addressed by mesh size regularization, which matches its size to the unit voxel of the volumetric data. We solve the model self-intersection problem by including a non-self-intersecting force among the customary internal and external forces in the physics-based formulation. This paper presents results of applying our new deformable model to extracting a sphere surface with concavities from a computer-generated volume data and a brain cortical surface from a MR volume data.

• Journal of the Korean Institute of Navigation
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• v.22 no.4
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• pp.37-44
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• 1998

This paper presents a procedure for automated extraction of ridge shadows in noisy gray images. This procedure mainly consists of 1) a deformable model which is designed basing upon the knowledge about the shape of shadows and is expected to be useful in extracting ridge shadows especially located in low signal to noise ratio background, and 2) the scale space scheme which is also useful even if there is less information about the size and the positions of ridge shadows in advance. This procedure is applied to artificial images and its performance is evaluated experimentally.