• 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 KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.589-600
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• 2002

Deformable models offer an attractive approach for extracting three-dimensional boundary structures from volumetric images. However, conventional deformable models have three major limitations - sensitive to initial condition, difficult to represent complex boundaries with severe object concavities and protrusions, and self-intersective between model elements. This paper proposes a deformable model that is effective to extract geometrically complex boundary surfaces by improving away the limitations of conventional deformable models. First, the proposed deformable model resamples its elements hierarchically based on volume image pyramid. The hierarchical resampling overcomes sensitivity to initialization by extracting the boundaries of objects in a multiscale scheme and enhances geometric flexibility to be well adapted to complex image features by refining and regularizing the size of model elements based on voxel size. Second, the physics-based formulation of our model integrates conventional internal and external forces, as well as a non-self-intersecting force. The non-self-intersecting force effectively prevents collision or crossing over between non-neighboring model elements by pushing each other apart if they are closer than a limited distance. We show that the proposed model successively extracts the complex boundaries including severe concavities and protrusions, neither depending on initial position nor causing self-intersection, through the experiments on several computer-generated volume images and brain MR volume images.

• 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.

• Journal of the Korean Society for Heat Treatment
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• v.27 no.5
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• pp.235-241
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• 2014

Effects of rolling and cooling conditions on microstructures and mechanical properties of high-deformable pipeline steels were investigated in this study. Six kinds of pipeline steels were fabricated by varying rolling and cooling conditions, and their microstructures were analyzed by scanning electron microscopy, electron back-scattered diffraction, and transmission electron microscopy. Tensile and Charpy impact tests were conducted on the steels in order to examine the mechanical properties. The steels rolled in the two-phase region showed better low-temperature toughness than those in the single-phase region due to the larger amount of ferrites having high-angle boundaries, although they have lower strength and absorbed energy. The steel rolled in single-phase and finish-cooled at higher temperature showed a good combination of high strength and good low-temperature toughness as well as excellent deformability of the lowest yield ratio and the highest uniform elongation because of the presence of fine ferrite and a mixture of various low-temperature transformation phases.

• Advances in nano research
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• v.15 no.4
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• pp.339-353
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• 2023

This work aims to present a solution for the buckling behavior of perforated nano/microbeams with deformable boundary conditions using nonlocal strain gradient theory (NLSGT). For the first time, a solution that can provide buckling loads based on the non-local and strain gradient effects of perforated nanostructures on an elastic foundation, while taking into account both deformable and rigid boundary conditions. Stokes' transformation and Fourier series are used to realize this aim and determine the buckling loads under various boundary conditions. We employ the NLSGT to account for size-dependent effects and utilize the Winkler model to formulate the elastic foundation. The buckling behavior of the perforated nano/microbeams restrained with lateral springs at both ends is studied for various parameters such as the number of holes, the length and filling ratio of the perforated beam, the internal length, the nonlocal parameter and the dimensionless foundation parameter. Our results indicate that the number of holes and filling ratio significantly affect the buckling response of perforated nano/microbeams. Increasing the filling ratio increases buckling loads, while increasing the number of holes decreases buckling loads. The effects of the non-local and internal length parameters on the buckling behavior of the perforated nano/microbeams are also discussed. These material length parameters have opposite effects on the variation of buckling loads. This study presents an effective eigenvalue solution based on Stokes' transformation and Fourier series of the restrained nano/microbeams under the effects of elastic medium, perforation parameters, deformable boundaries and nonlocal strain gradient elasticity for the first time.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.6
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• pp.829-836
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• 2001

A dependable boundary reconstruction technique is proposed. The finite element method is used for the analysis of the direct heat conduction problem to realize the deformable grid system. An appropriate strategy for grid update is suggested. A complete sensitivity analysis is performed to obtain the derivatives required for restoration of the optimal boundary. With the result of the sensitivity analysis, the unknown boundary is sought using the sequential quadratic programming. The method is applied to reconstruction of boundaries with sinusoidal, step, and cavity form. The overall performance of the proposed method is examined by comparison between the estimated the exact boundaries.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.17-31
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• 2002

The new MPEG-4 video coding standard enables content-based functionalities. Image segmentation is an indispensable process for it. This paper addresses an effective segmentation of non-rigid objects. Non-rigid objects are deformable objects with fuzzy, blurred and indefinite boundaries. So it is difficult to segment deformable objects precisely. In order to solve this problem, we propose an effective segmentation of non-rigid objects using watershed algorithms in still pictures. And we propose an automatic segmentation through intra-frame and inter-frame segmentation process in video sequences. Automatic segmentation preforms boundary-based and region-based segmentation to extract precise object boundaries.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.437-452
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• 2022

For the first time, the higher-order shear and normal deformable plate theory (HOSNDPT) is used for the vibration and flutter analyses of the multilayer functionally graded graphene platelets reinforced composite (FG-GPLRC) plates under supersonic airflow. For modeling the supersonic airflow, the linear piston theory is adopted. In HOSNDPT, Legendre polynomials are used to approximate the components of the displacement field in the thickness direction. So, all stress and strain components are encountered. Either uniform or three kinds of non-uniform distribution of graphene platelets (GPLs) into polymer matrix are considered. The Young modulus of the FG-GPLRC plate is estimated by the modified Halpin-Tsai model, while the Poisson ratio and mass density are determined by the rule of mixtures. The Hamilton's principle is used to obtain the governing equations of motion and the associated boundary conditions of the plate. For solving the plate's equations of motion, the Galerkin approach is applied. A comparison for the natural frequencies obtained based on the present investigation and those of three-dimensional elasticity theory shows a very good agreement. The flutter boundaries for FG-GPLRC plates based on HOSNDPT are described and the effects of GPL distribution patterns, the geometrical parameters and the weight fraction of GPLs on the flutter frequencies and flutter aerodynamic pressure of the plate are studied in detail. The obtained results show that by increasing 0.5% of GPLs into polymer matrix, the flutter aerodynamic pressure increases approximately 117%, 145%, 166% and 196% for FG-O, FG-A, UD and FG-X distribution patterns, respectively.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.