• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.925-930
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• 2002

This paper discusses techniques for embedding data into 3D polygonal models of geometry. Much researches of Watermarking had been gone as element technology of DRM (digital rights management). But, few research had gone to 3D polygonal model. Most research is limited at text document, 2D image, animation, music etc. RP system is suitable a few production in various goods species, and it is used much in industry to possible reason that produce prototype and find error or incongruent factor at early stage on design in product development childhood. This paper is research about method that insert watermark in STL ( stereolithography) file that have 3D shape model. Proposed algorithm inserts watermark in normal vector region and facet's interior region of 3D shape data. For this reason, 3D shape does not produce some flexure and fulfill invisibility of watermark. Experiment results that insert and extract watermark in normal netter region and facet's Interior region of 3D shape data by proposed algorithm do not influence entirely in 3D shape and show that insertion and extraction of watermark are possible.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.8
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• pp.449-456
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• 2002

3D Equivalent magnetic Circuit Network Method (EMCNM) is comparatively the easy way that analyzes 3D models of Electric Machine by using permeance as a distributive magnetic circuit parameter under the existing magnetic equivalent circuit method and Numerical Method. The existing 3D EMCNM could not correctly describe the shape of an analysis target when using rectangular shape element or fan shape element, so it made errors when calculating permeance. Therefore, this paper proposes the trapezoidal element contained rectangular element, fan-shape element, and quadrilateral element to express a shape. The proposed method in this research was confirmed as a useful and an accurate method through comparing with the analysis result of SRM model that is sufficiently guaranteed by 2D-Analysis.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.397-410
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• 2007

Visualization of 2D and 3D data, which arises from some scientific phenomena, physical model or mathematical formula, in the form of curve or surface view is one of the important topics in Computer Graphics. The problem gets critically important when data possesses some inherent shape feature. For example, it may have positive feature in one instance and monotone in the other. This paper is concerned with the solution of similar problems when data has convex shape and its visualization is required to have similar inherent features to that of data. A rational cubic function [5] has been used for the review of visualization of 2D data. After that it has been generalized for the visualization of 3D data. Moreover, simple sufficient constraints are made on the free parameters in the description of rational bicubic functions to visualize the 3D convex data in the view of convex surfaces.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

In this paper, we analyze geometrical relations of 3D shape reconstruction from 2D images taken under anne projection. The purpose of this research is to contribute to more accurate 3-D reconstruction under noise distribution by analyzing geometrically the 2D to 3D relationship. In situation for no missing feature points (FPs) or no noise in 2D image plane, the accurate solution of 3D shape reconstruction is blown to be provided by Singular Yalue Decomposition (SVD) factorization. However, if several FPs not been observed because of object occlusion and image low resolution, and so on, there is no simple solution. Moreover, the 3D shape reconstructed from noise-distributed FPs is peturbed because of the influence of the noise. This paper focuses on analysis of geometrical properties which can interpret the missing FPs even though the noise is distributed on other FPs.

• Korean Journal of Computational Design and Engineering
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• v.8 no.2
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• pp.122-132
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• 2003

STEP AP218 has a standard schema to represent the structural model of a midship section. While it helps to exchange ship structural models among heterogeneous automation systems, most shipyards and classification societies still exchange information using 2D paper drawings. We propose a feature parameter input method to generate a 3D STEP model of a ship structure from 2D drawings. We have analyzed the ship structure information contained in 2D drawings and have defined a data model to express the contents of the drawing. We also developed a QUI for the feature parameter input. To translate 2D information extracted from the drawing into a STEP AP2l8 model, we have developed a shape generation library, and generated the 3D ship model through this library. The generated 3D STEP model of a ship structure can be used to exchange information between design departments in a shipyard as well as between classification societies and shipyards.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.185-191
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• 2009

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship betweenfeatures, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

• Steel and Composite Structures
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• v.33 no.5
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• pp.747-753
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• 2019

Metaheuristic algorithm is used to solve the weight minimization problem of truss structures considering shape, and sizing design variables. The cross-sectional areas of the line element in trusses are the design variables for size optimization and the changeable joint coordinates are the shape optimization used in this study. The design of plane and spatial truss structures are optimized by metaheuristic technique named Teaching-Learning-Based Optimization (TLBO). Finite element analyses of structures and optimization process are carried out by the computer program visually developed by the authors coded in MATLAB. The four benchmark problems (trusses 2D ten-bar, 3D thirty-seven-bar, 3D seventy-two-bar and 2D two-hundred-bar) taken from literature are optimized and the optimal solution compared the results given by previous studies.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.81-93
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• 1993

The three dimensional(3D) shape reconstruction from two dimensional(2D) cross-sections can be completed through three main phases : the input compilation, the triangular grid formation, and the smooth surface construction. In the input compilation phase, the cross-sections are analyzed to exctract the input data required for the shape reconstruction. This data includes the number of polygonized contours per cross-section and the vertices defining each polygonized contour. In the triangular grid formation phase, a triangular grid, leading to a polyhedral approximations, is constructed by extracting all the information concerning contour links between two adjacent cross- sections and then performing the appropriate triangulation procedure for each contour link. In the smooth surface construction phase, a smooth composite surface interpolating all vertices on the triangular grid is constructed. Both the smooth surface and the polyhedral approximation can be used as reconstructed models of the object. This paper proposes a new method for reconstructing the geometric model of a 3D objdect from a sequence of planar contours representing 2D cross-sections of the objdect. The method includes the triangular grid formation algorithms for contour closing, one-to-one branching, and one-to-many braanching, and many-to-many branching. The shape reconstruction method has been implemented on a SUN workstation in C.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.391-396
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• 2008

Motion of object in a video clip often plays an important role in characterizing the content of the clip. A number of methods have been developed to analyze and retrieve video contents using motion information. However, most of these methods focused more on the analysis of direction or trajectory of motion but less on the analysis of the movement of an object itself. In this paper, we propose the shape sequence descriptor to describe and compare the movement based on the shape deformation caused by object motion along the time. A movement information is first represented a sequence of 2D shape of object extracted from input image sequence, and then 2D shape information is converted 1D shape feature using the shape descriptor. The shape sequence descriptor is obtained from the shape descriptor sequence by frequency transform along the time. Our experiment results show that the proposed method can be very simple and effective to describe the object movement and can be applicable to semantic applications such as content-based video retrieval and human movement recognition.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.66-71
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• 2019

In shape from focus (SFF) methods, the quality of image focus volume plays a vital role in the quality of 3D shape reconstruction. Traditionally, a linear 2D filter is applied to each slice of the image focus volume to rectify the noisy focus measurements. However, this approach is problematic because it also modifies the accurate focus measurements that should ideally remain intact. Therefore, in this paper, we propose to enhance the focus volume adaptively by applying 3-dimensional weighted least squares (3D-WLS) based regularization. We estimate regularization weights from the guidance volume extracted from the image sequences. To solve 3D-WLS optimization problem efficiently, we apply a technique to solve a series of 1D linear sub-problems. Experiments conducted on synthetic and real image sequences demonstrate that the proposed method effectively enhances the image focus volume, ultimately improving the quality of reconstructed shape.