• 한국정밀공학회지
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• 제26권12호
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• pp.138-145
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• 2009

Custom medical treatment is being widely adapted to lots of medical applications. A technology for 3D modeling is strongly required to fabricate medical implants for individual patient. Needs on true 3D CAD data of a patient is strongly required for tissue engineering and human body simulations. Medical imaging devices show human inner section and 3D volume rendering images of human organs. CT or MRI is one of the popular imaging devices for that use. However, those image data is not sufficient to use for medical fabrication or simulation. This paper mainly deals how to generate 3D geometry data from those medical images. A new image processing technology is introduced to reconstruct 3D geometry of a human body vacancy from the medical images. Then a surface geometry data is reconstructed by using Marching cube algorithm. Resulting CAD data is a custom 3D geometry data of human vacancy. This paper introduces a novel 3D reconstruction process and shows some typical examples with implemented software.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1989년도 춘계학술대회
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• pp.55-59
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• 1989

A true three-dimensional cone-beam reconstruction (TTCR) algorithm for the complete sphere geometry is derived, which is applicable to the direct volume image reconstruction from 2-D cone-beam projections. The algorithm is based on the modified filtered backprojection technique which uses a set of 2-D space-invariant filters and is derived from the previously developed parallel-beam true three-dimensional reconstruction(TTR) algorithm. The proposed algorithm proved to be superior in spatial resolution compared with the parallel-beam TTR algorithm.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.59-64
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• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.182-185
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• 2005

Satellite cameras are calibrated before launch in detail and in general, but it cannot be guaranteed that the geometry is not changing during launch and caused by thermal influence of the sun in the orbit. Modem satellite imaging systems are based on CCD-line sensors. Because of the required high sampling rate the length of used CCD-lines is limited. For reaching a sufficient swath width, some CCD-lines are combined to a longer virtual CCD-line. The images generated by the individual CCD-lines do overlap slightly and so they can be shifted in x- and y-direction in relation to a chosen reference image just based on tie points. For the alignment and difference in scale, control points are required. The resulting virtual image has only negligible errors in areas with very large difference in height caused by the difference in the location of the projection centers. Color images can be related to the joint panchromatic scenes just based on tie points. Pan-sharpened images may show only small color shifts in very mountainous areas and for moving objects. The direct sensor orientation has to be calibrated based on control points. Discrepancies in horizontal shift can only be separated from attitude discrepancies with a good three-dimensional control point distribution. For such a calibration a program based on geometric reconstruction of the sensor orientation is required. The approximations by 3D-affine transformation or direct linear transformation (DL n cannot be used. These methods do have also disadvantages for standard sensor orientation. The image orientation by geometric reconstruction can be improved by self calibration with additional parameters for the analysis and compensation of remaining systematic effects for example caused by a not linear CCD-line. The determined sensor geometry can be used for the generation? of rational polynomial coefficients, describing the sensor geometry by relations of polynomials of the ground coordinates X, Y and Z.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.435-449
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• 2023

The state-of-the-art video-based point cloud compression(V-PCC) has a high efficiency of compressing 3D point cloud by projecting points onto 2D images. These images are then padded and compressed by High-Efficiency Video Coding(HEVC). Pixels in padded 2D images are classified into three groups including origin pixels, padded pixels and unoccupied pixels. Origin pixels are generated from projection of 3D point cloud. Padded pixels and unoccupied pixels are generated by copying values from origin pixels during image padding. For padded pixels, they are reconstructed to 3D space during geometry reconstruction as well as origin pixels. For unoccupied pixels, they are not reconstructed. The rate distortion optimization(RDO) used in HEVC is mainly aimed at keeping the balance between video distortion and video bitrates. However, traditional RDO is unreliable for padded pixels and unoccupied pixels, which leads to significant waste of bits in geometry reconstruction. In this paper, we propose a new RDO scheme which takes 3D-Distortion into account instead of traditional video distortion for padded pixels and unoccupied pixels. Firstly, these pixels are classified based on the occupancy map. Secondly, different strategies are applied to these pixels to calculate their 3D-Distortions. Finally, the obtained 3D-Distortions replace the sum square error(SSE) during the full RDO process in intra prediction and inter prediction. The proposed method is applied to geometry frames. Experimental results show that the proposed algorithm achieves an average of 31.41% and 6.14% bitrate saving for D1 metric in Random Access setting and All Intra setting on geometry videos compared with V-PCC anchor.

• 호남수학학술지
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• 제36권4호
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• pp.831-852
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• 2014

The obstacle shape reconstruction problem has been known to be difficult to solve since it is highly nonlinear and severely ill-posed. The use of local or locally supported basis functions for the problem has been addressed for many years. However, to the authors' knowledge, any research report on the proper usage of local or locally supported basis functions for the shape reconstruction has not been appeared in the literature due to many difficulties. The aim of this paper is to introduce the general concepts and methodologies for the proper choice and their implementation of locally supported basis functions through the two-dimensional Helmholtz equation. The implementations are based on the complex nonlinear parameter estimation (CNPE) formula and its robust algorithm developed recently by the authors. The basic concepts and ideas are simple. The derivation of the necessary properties needed for the shape reconstructions are elementary. However, the capturing abilities for the local geometry of the obstacle are superior to those by conventional methods, the trial and errors, due to the proper implementation and the CNPE algorithm. Several numerical experiments are performed to show the power of the proposed method. The fundamental ideas and methodologies described in this paper can be applied to many other shape reconstruction problems.

• 대한기계학회논문집A
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• 제29권4호
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.63.3-63
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• 2001

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. In this paper, we propose a three dimensional volume reconstruction method, which is an iterative method and as uniform and simulated algebraic reconstruction technique (USART). In this method, two or more x-ray images projected from different views are needed, and also the geometry of the imaging system need to be a priori identified well. That is to say, the relative locations between the x-ray source, imaging plane and the object should be determined exactly by calibration. To achieve this, we propose a series of coordinate calibration methods of the x-ray imaging system using grid pattern images. Some experimental results of these calibrations is presented and discussed in detail ...

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.183-186
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• 2003

A vision sensor should be calibrated prior to infer a Euclidian shape reconstruction. A point to point calibration. also referred to as a hard calibration, estimates calibration parameters by means of a set of 3D to 2D point pairs. We proposed a new method for determining a set of 3D to 2D pairs for the structured light hard calibration. It is simply determined based on epipolar geometry between camera image plane and projector plane, and a projector calibrating grid pattern. The projector calibration is divided two stages; world 3D data acquisition Stage and corresponding 2D data acquisition stage. After 3D data points are derived using cross ratio, corresponding 2D point in the projector plane can be determined by the fundamental matrix and horizontal grid ID of a projector calibrating pattern. Euclidian reconstruction can be achieved by linear triangulation. and experimental results from simulation are presented.

• IEIE Transactions on Smart Processing and Computing
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• 제3권2호
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• pp.59-64
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• 2014

This paper presents a method for estimating the bounding volume for image-based 3D object reconstruction. The bounding volume of an object is a three-dimensional space where the object is expected to exist, and the size of the bounding volume strongly affects the resolution of the reconstructed geometry. Therefore, the size of a bounding volume should be as small as possible while it encloses an actual object. To this end, the proposed method uses a set of silhouettes of an object and generates a point cloud using a point filter. A bounding volume is then determined as the minimum sphere that encloses the point cloud. The experimental results show that the proposed method generates a bounding volume that encloses an actual object as small as possible.