• Title/Summary/Keyword: voxelization

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Voxelization based on graphics API(Application Program Interface) (그래픽스 API를 이용한 복셀화)

  • 정현배;송주환;권오봉;최성희
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.550-552
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    • 2001
  • 본 논문은 3차원 그래픽스 시스템이 기본적으로 제공하는 프리미티브인 면(surface), 솔리드(solid)의 복셀화 및 이들을 결합한 CSG 표현의 복셀화에 대하여 고찰한다. 복셀화는 서피스로 표현된 물체의 빈 내부를 복셀로 표현하여 내부를 태우는 과정이다. 본 방법의 특징은 PC 플랫폼이 제공하는 그래픽스 API인 OpenGL을 이용하여 면, 솔리드 등을 고속으로 복셀화하여 이들을 기본 물체로 하여 불리언연산에 의해서 간단히 새로운 물체를 만들고 볼륨 환경에서 이들을 단일화된 방법으로 렌더링할 수 있는 것이다.

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Graph Representation by Medial Axis Transform Image for 3D Retrieval (3차원 영상 검색을 위한 중심축 변환에 의한 그래프 표현 기법)

  • Kim, Deok-Hun;Yun, Il-Dong;Lee, Sang-Uk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.1
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    • pp.33-42
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    • 2001
  • Recently, the interests in the 3D image, generated from the range data and CAD, have exceedingly increased, accordingly a various 3D image database is being constructed. The efficient and fast scheme to access the desired image data is the important issue in the application area of the Internet and digital library. However, it is difficult to manage the 3D image database because of its huge size. Therefore, a proper descriptor is necessary to manage the data efficiently, including the content-based search. In this paper, the proposed shape descriptor is based on the voxelization of the 3D image. The medial axis transform, stemming from the mathematical morphology, is performed on the voxelized 3D image and the graph, which is composed of node and edge, is generated from skeletons. The generated graph is adequate to the novel shape descriptor due to no loss of geometric information and the similarity of the insight of the human. Therefore the proposed shape descriptor would be useful for the recognition of 3D object, compression, and content-based search.

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Volume Data Modeling by Using Wavelets Transformation and Tetrahedrization (웨이브렛 변환과 사면체 분할을 이용한 볼륨 데이터 모델링)

  • Gwun, Ou-Bong;Lee, Kun
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.4
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    • pp.1081-1089
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    • 1999
  • Volume data modeling is concerned with finding a mathematical function which represents the relationship implied by the 3D data. Modeling a volume data geometrically can visualize a volume data using surface graphics without voxelization. It has many merits in that it is fast and requires little memory. We proposes, a method based on wavelet transformation and tetrahedrization. we implement a prototype system based on the proposed method. Last, we evaluated the proposed method comparing it with marching cube algorithm. the evaluation results show that though the proposed method uses only 13% of the volume data, the images generated is as good as the images generated by the marching cubes algorithm.

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Efficient Calculation of Trapped Volumes in Layered Manufacturing Process (적층 성형 과정에서 고립 체적의 효율적 계산)

  • 김진영;이건우;정융호
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.2
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    • pp.154-161
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    • 1998
  • Prototypes of a design are always needed for the purpose of visualization and evaluation in the aspect of manufacturability functionality, and aesthetic appearance. Since the prototyping process requires a significant amount of cost and time, various rapid prototyping processes are recently being introduced in the process. However, it is usually necessary for a part built up by a rapid prototyping system to be refined by a post-processing process, in which the stair steps on the surfaces, the support structures (if they exist), and the unprocessed material are eliminated. This post-processing is usually done manually and is a time-consuming task. Especially, eliminating the trapped volumes, the volume of the unprocessed material entrapped by the solidified portion, is sometimes impossible in some processes. This study provides a designer with a tool to detect the existence and to calculate the quantity of the trapped volumes at the given build-up direction, so that the proper build-up direction is chosen or the part is built by pieces to avoid the problems caused by the trapped volumes in advance. Since the proposed algorithm can efficiently calculate the amount of the trapped volumes at any build-up direction, it has the potential of such application as optimizing the build-up direction to minimize the trapped volumes.

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Positional correction of a 3D position-sensitive virtual Frisch-grid CZT detector for gamma spectroscopy and imaging based on a theoretical assumption

  • Younghak Kim ;Kichang Shin ;Aleksey Bolotnikov;Wonho Lee
    • Nuclear Engineering and Technology
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    • v.55 no.5
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    • pp.1718-1733
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    • 2023
  • The virtual Frisch-grid method for room-temperature radiation detectors has been widely used because of its simplicity and high performance. Recently, side electrodes were separately attached to each surface of the detectors instead of covering the entire detector surface with a single electrode. The side-electrode structure enables the measurement of the three-dimensional (3D) gamma-ray interaction in the detector. The positional information of the interaction can then be utilized to precisely calibrate the response of the detector for gamma-ray spectroscopy and imaging. In this study, we developed a 3D position-sensitive 5 × 5 × 12 mm3 cadmium-zinc-telluride (CZT) detector and applied a flattening method to correct detector responses. Collimated gamma-rays incident on the surface of the detector were scanned to evaluate the positional accuracy of the detection system. Positional distributions of the radiation interactions with the detector were imaged for quantitative and qualitative evaluation. The energy spectra of various radioisotopes were measured and improved by the detector response calibration according to the calculated positional information. The energy spectra ranged from 59.5 keV (emitted by 241Am) to 1332 keV (emitted by 60Co). The best energy resolution was 1.06% at 662 keV when the CZT detector was voxelized to 20 × 20 × 10.

TET2DICOM-GUI: Graphical User Interface Based TET2DICOM Program to Convert Tetrahedral-Mesh-Phantom to DICOM-RT Dataset

  • Se Hyung Lee;Bo-Wi Cheon;Chul Hee Min;Haegin Han;Chan Hyeong Kim;Min Cheol Han;Seonghoon Kim
    • Progress in Medical Physics
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    • v.33 no.4
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    • pp.172-179
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    • 2022
  • Recently, tetrahedral phantoms have been newly adopted as international standard mesh-type reference computational phantoms (MRCPs) by the International Commission on Radiological Protection, and a program has been developed to convert them to computational tomography images and DICOM-RT structure files for application of radiotherapy. Through this program, the use of the tetrahedral standard phantom has become available in clinical practice, but utilization has been difficult due to various library dependencies requiring a lot of time and effort for installation. To overcome this limitation, in this study a newly developed TET2DICOM-GUI, a TET2DICOM program based on a graphical user interface (GUI), was programmed using only the MATLAB language so that it can be used without additional library installation and configuration. The program runs in the same order as TET2DICOM and has been optimized to run on a personal computer in a GUI environment. A tetrahedron-based male international standard human phantom, MRCP-AM, was used to evaluate TET2DICOM-GUI. Conversion into a DICOM-RT dataset applicable in clinical practice in about one hour with a personal computer as a basis was confirmed. Also, the generated DICOM-RT dataset was confirmed to be effectively implemented in the radiotherapy planning system. The program developed in this study is expected to replace actual patient data in future studies.

Reconfiguration of Physical Structure of Vegetation by Voxelization Based on 3D Point Clouds (3차원 포인트 클라우드 기반 복셀화에 의한 식생의 물리적 구조 재구현)

  • Ahn, Myeonghui;Jang, Eun-kyung;Bae, Inhyeok;Ji, Un
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.571-581
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    • 2020
  • Vegetation affects water level change and flow resistance in rivers and impacts waterway ecosystems as a whole. Therefore, it is important to have accurate information about the species, shape, and size of any river vegetation. However, it is not easy to collect full vegetation data on-site, so recent studies have attempted to obtain large amounts of vegetation data using terrestrial laser scanning (TLS). Also, due to the complex shape of vegetation, it is not easy to obtain accurate information about the canopy area, and there are limitations due to a complex range of variables. Therefore, the physical structure of vegetation was analyzed in this study by reconfiguring high-resolution point cloud data collected through 3-dimensional terrestrial laser scanning (3D TLS) in a voxel. Each physical structure was analyzed under three different conditions: a simple vegetation formation without leaves, a complete formation with leaves, and a patch-scale vegetation formation. In the raw data, the outlier and unnecessary data were filtered and removed by Statistical Outlier Removal (SOR), resulting in 17%, 26%, and 25% of data being removed, respectively. Also, vegetation volume by voxel size was reconfigured from post-processed point clouds and compared with vegetation volume; the analysis showed that the margin of error was 8%, 25%, and 63% for each condition, respectively. The larger the size of the target sample, the larger the error. The vegetation surface looked visually similar when resizing the voxel; however, the volume of the entire vegetation was susceptible to error.

Attention based Feature-Fusion Network for 3D Object Detection (3차원 객체 탐지를 위한 어텐션 기반 특징 융합 네트워크)

  • Sang-Hyun Ryoo;Dae-Yeol Kang;Seung-Jun Hwang;Sung-Jun Park;Joong-Hwan Baek
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.190-196
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    • 2023
  • Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.