• Title/Summary/Keyword: 점군(點群)

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Feature-based Matching Algorithms for Registration between LiDAR Point Cloud Intensity Data Acquired from MMS and Image Data from UAV (MMS로부터 취득된 LiDAR 점군데이터의 반사강도 영상과 UAV 영상의 정합을 위한 특징점 기반 매칭 기법 연구)

  • Choi, Yoonjo;Farkoushi, Mohammad Gholami;Hong, Seunghwan;Sohn, Hong-Gyoo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.453-464
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    • 2019
  • Recently, as the demand for 3D geospatial information increases, the importance of rapid and accurate data construction has increased. Although many studies have been conducted to register UAV (Unmanned Aerial Vehicle) imagery based on LiDAR (Light Detection and Ranging) data, which is capable of precise 3D data construction, studies using LiDAR data embedded in MMS (Mobile Mapping System) are insufficient. Therefore, this study compared and analyzed 9 matching algorithms based on feature points for registering reflectance image converted from LiDAR point cloud intensity data acquired from MMS with image data from UAV. Our results indicated that when the SIFT (Scale Invariant Feature Transform) algorithm was applied, it was able to stable secure a high matching accuracy, and it was confirmed that sufficient conjugate points were extracted even in various road environments. For the registration accuracy analysis, the SIFT algorithm was able to secure the accuracy at about 10 pixels except the case when the overlapping area is low and the same pattern is repeated. This is a reasonable result considering that the distortion of the UAV altitude is included at the time of UAV image capturing. Therefore, the results of this study are expected to be used as a basic research for 3D registration of LiDAR point cloud intensity data and UAV imagery.

Three Dimensional Metrology of Surface Mounted Solder Pastes Using Bounding Box Formed by Histogram of Gradient Vectors of Point Cloud (점군의 기울기벡터 히스토그램에 의해 형성된 구속상자를 이용한 표면실장 솔더페이스트의 3차원 Metrology)

  • 신동원
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.674-677
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    • 2003
  • This work presents a method of point-to-surface assignment for 3D inspection of solder pastes on PCB. A bounding box enclosing the solder paste tightly on all sides is introduced to avoid incorrect point-to-surface assignment. The shape of bounding box for solder paste brick is variable according to geometry of measured points. The surface geometry of the bounding box is obtained by using five peaks selected from the histogram of normalized gradient vectors for measured points. By using the bounding box enclosing the solder paste. the task of point-to-surface assignment is successfully executed. Subsequently, the geometrical features are obtained via surface fitting.

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Point Cloud Slicing Based on 2D Delaunay Triangulation (2D Delaunay Triangulation을 이용한 점군 절단)

  • Park, Hyeong-Tae;Chang, Min-Ho;Park, Sang-Chul
    • Journal of the Korean Society for Precision Engineering
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    • v.24 no.5
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    • pp.127-134
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    • 2007
  • Presented in the paper is an algorithm to generate a section curve by slicing a point cloud including tens of thousands of points. Although, there have been previous research results on the slicing problem, they are quite sensitive on the density variations of the point cloud, as well as on the local noise in the point cloud. To relive the difficulties, three technological requirements are identified; 1) dominant point sampling, 2) avoiding local vibration, and 3) robustness on the density changes. To satisfy these requirements, we propose a new slicing algorithm which is based on a node-sphere diagram. The algorithm has been implemented and tested with various examples.

Volume Detection from Indoor Spherical Panorama Point Cloud (실내 구면 파노라마 점군으로부터의 볼륨 검출)

  • Kim, Ki-Sik;Park, Jong-Seung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.560-563
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    • 2021
  • 본 논문에서는 사각형 실내 공간에서 점군 데이터를 기반으로 빠르고 정확하게 바닥, 천장, 벽면에 대한 평면 정보를 획득할 수 있는 시스템을 제안한다. 기존의 방법은 관측되지 않은 공간에 대한 평면을 예측할 수 없으며, 노이즈에 취약하고, 모든 점에 대한 기저 정보를 알아야하기 때문에 많은 연산량을 요구한다. 제안 방법은 기존의 평면 검출 방식에서 벗어나 Bounding Box 형상을 예측하는 기술을 활용한다. 또한, 제안 시스템은 구면 파노라마 비디오를 기반으로 적은 수의 프레임으로도 빠르게 실시간 점군 데이터를 확장해나간다. 제안 방법은 실험을 통해 기존의 방법보다 월등히 빠르고, 노이즈 등 환경 제약 요소에 강건함을 보인다.

High Quality Ortho-image Production Using the High Resolution DMCII Aerial Image (고해상도 DMCII 항공영상을 이용한 고품질 정사영상 제작)

  • Kim, Jong Nam;Um, Dae Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.1
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    • pp.11-21
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    • 2015
  • An Ortho-image is the production of removed geometrical displacement, which is generated the aerial image distortion and the relief displacement, etc., using the DSM (Digital Surface Model). Accordingly, the resolution of raw image and the accuracy of DSM will has significant impacts on the ortho-image accuracy. Since the latest DMCII250 aerial camera delivers the high resolution images with five centimeters Ground Sampling Distance(GSD), it expects to generate the high density point clouds and the high quality ortho-images. Therefore, this research has planned for reviewing the potentiality and accuracy of high quality ortho-image production. Following to proceed the research, DSM has been produced through the high density point cloud extracted from DMCII250 aerial image to supply of high density DSM by creation of ortho-image. The research results has been identified that images with the DSM brought out higher degrees in positional accuracy and quality of ortho-image, compared with the ortho-image, produced from the existing digital terrain map or DSM data.

A Study on Building Identification from the Three-dimensional Point Cloud by using Monte Carlo Integration Method (몬테카를로 적분을 통한 3차원 점군의 건물 식별기법 연구)

  • YI, Chaeyeon;AN, Seung-Man
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.16-41
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    • 2020
  • Geospatial input setting to represent the reality of spatial distribution or quantitative property within model has become a major interest in earth system simulation. Many studies showed the variation of grid resolution could lead to drastic changes of spatial model results because of insufficient surface property estimations. Hence, in this paper, the authors proposed Monte Carlo Integration (MCI) to apply spatial probability (SP) in a spatial-sampling framework using a three-dimensional point cloud (3DPC) to keep the optimized spatial distribution and area/volume property of buildings in urban area. Three different decision rule based building identification results were compared : SP threshold, cell size, and 3DPC density. Results shows the identified building area property tend to increase according to the spatial sampling grid area enlargement. Hence, areal building property manipulation in the sampling frameworks by using decision rules is strongly recommended to increase reliability of geospatial modeling and analysis results. Proposed method will support the modeling needs to keep quantitative building properties in both finer and coarser grids.

Development of Mean Stand Height Module Using Image-Based Point Cloud and FUSION S/W (영상 기반 3차원 점군과 FUSION S/W 기반의 임분고 분석 모듈 개발)

  • KIM, Kyoung-Min
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.4
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    • pp.169-185
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    • 2016
  • Recently mean stand height has been added as new attribute to forest type maps, but it is often too costly and time consuming to manually measure 9,100,000 points from countrywide stereo aerial photos. In addition, tree heights are frequently measured around tombs and forest edges, which are poor representations of the interior tree stand. This work proposes an estimation of mean stand height using an image-based point cloud, which was extracted from stereo aerial photo with FUSION S/W. Then, a digital terrain model was created by filtering the DSM point cloud and subtracting the DTM from DSM, resulting in nDSM, which represents object heights (buildings, trees, etc.). The RMSE was calculated to compare differences in tree heights between those observed and extracted from the nDSM. The resulting RMSE of average total plot height was 0.96 m. Individual tree heights of the whole study site area were extracted using the USDA Forest Service's FUSION S/W. Finally, mean stand height was produced by averaging individual tree heights in a stand polygon of the forest type map. In order to automate the mean stand height extraction using photogrammetric methods, a module was developed as an ArcGIS add-in toolbox.