• Title/Summary/Keyword: Automatic surface matching

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Automatic Surface Matching for the Registration of LIDAR Data and MR Imagery

  • Habib, Ayman F.;Cheng, Rita W.T.;Kim, Eui-Myoung;Mitishita, Edson A.;Frayne, Richard;Ronsky, Janet L.
    • ETRI Journal
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    • v.28 no.2
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    • pp.162-174
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    • 2006
  • Several photogrammetric and geographic information system applications such as surface matching, object recognition, city modeling, environmental monitoring, and change detection deal with multiple versions of the same surface that have been derived from different sources and/or at different times. Surface registration is a necessary procedure prior to the manipulation of these 3D datasets. This need is also applicable in the field of medical imaging, where imaging modalities such as magnetic resonance imaging (MRI) can provide temporal 3D imagery for monitoring disease progression. This paper will present a general automated surface registration procedure that can establish correspondences between conjugate surface elements. Experimental results using light detection and ranging (LIDAR) and MRI data will verify the feasibility, robustness, and accuracy of this approach.

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AUTOMATIC BUILDING EXTRACTION BASED ON MULTI-SOURCE DATA FUSION

  • Lu, Yi Hui;Trinder, John
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.248-250
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    • 2003
  • An automatic approach and strategy for extracting building information from aerial images using combined image analysis and interpretation techniques is described in this paper. A dense DSM is obtained by stereo image matching. Multi-band classification, DSM, texture segmentation and Normalised Difference Vegetation Index (NDVI) are used to reveal building interest areas. Then, based on the derived approximate building areas, a shape modelling algorithm based on the level set formulation of curve and surface motion has been used to precisely delineate the building boundaries. Data fusion, based on the Dempster-Shafer technique, is used to interpret simultaneously knowledge from several data sources of the same region, to find the intersection of propositions on extracted information derived from several datasets, together with their associated probabilities. A number of test areas, which include buildings with different sizes, shape and roof colour have been investigated. The tests are encouraging and demonstrate that the system is effective for building extraction, and the determination of more accurate elevations of the terrain surface.

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Image Matching Method of Digital Surface Model Generation for Built-up Area (건물지역 수치표면모형 자동생성을 위한 영상정합 방법)

  • 박희주
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.18 no.3
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    • pp.315-322
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    • 2000
  • DSM(Digital Surface Model) is a digital model which represents the surface elevation of a region. DSM is necessary for orthoimage generation, and frequently used in man-made object extraction from aerial photographs nowadays. Image matching technique enables automatic DSM generation. This proposed a image matching method which can be applied to automatic generation of DSM for Built-up Area. The matching method proposed is to find conjugate points and conjugate lines from overlapping aerial images. In detecting conjugate points, the positional relation between possible conjugate point pair as well as correlation of pixel gray value is compared. In detecting conjugate lines, the color attribute of flank region of line, shape of line, positional relation between neighborhood points and lines, and the connection relation between lines are compared. The proposed matching method is assumed to be useful for DSM generation including Built-up Area.

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3D VISION SYSTEM FOR THE RECOGNITION OF FREE PARKING SITE LOCATION

  • Jung, H.G.;Kim, D.S.;Yoon, P.J.;Kim, J.H.
    • International Journal of Automotive Technology
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    • v.7 no.3
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    • pp.361-367
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    • 2006
  • This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

Highly Dense 3D Surface Generation Using Multi-image Matching

  • Noh, Myoung-Jong;Cho, Woo-Sug;Bang, Ki-In
    • ETRI Journal
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    • v.34 no.1
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    • pp.87-97
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    • 2012
  • This study presents an automatic matching method for generating a dense, accurate, and discontinuity-preserved digital surface model (DSM) using multiple images acquired by an aerial digital frame camera. The proposed method consists of two main procedures: area-based multi-image matching (AMIM) and stereo-pair epipolar line matching (SELM). AMIM evaluates the sum of the normalized cross correlation of corresponding image points from multiple images to determine the optimal height of an object point. A novel method is introduced for determining the search height range and incremental height, which are necessary for the vertical line locus used in the AMIM. This procedure also includes the means to select the best reference and target images for each strip so that multi-image matching can resolve the common problem over occlusion areas. The SELM extracts densely positioned distinct points along epipolar lines from the multiple images and generates a discontinuity-preserved DSM using geometric and radiometric constraints. The matched points derived by the AMIM are used as anchor points between overlapped images to find conjugate distinct points using epipolar geometry. The performance of the proposed method was evaluated for several different test areas, including urban areas.

Automatic Generation of Roughing Tool Path upon Unequal Level Line Matching (비균등분할 등고선 가공법에 의한 황삭가공경로의 자동생성)

  • Kim, Byeong-Hee
    • Journal of Industrial Technology
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    • v.15
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    • pp.23-32
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    • 1995
  • The methodology of automatic generation of tool path for rough cutting of a sculptured surface is proposed with the improved contouring method, unequal level line machining. Considering the surface shape and the diameter of the endmill, the distance between level lines is obtained. To improve MMR, initial rough cutting is processed with the large diameter endmill and the remained material is removed by the relatively small diameter endmill. Tool path is generated from the offset curve of respective level line and the interferences between the tool and workpiece are automatically avoided. After generating NC part program, the sculptured surface is machined at the vertical machining center. From the experimental results, total cutting length and machining time are reduced more effectively than conventional contouring methods.

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Pattern Matching for Automatic Defects Detection of the Light Guide Panel (도광판의 자동 결함 검출을 위한 패턴 매칭)

  • Cho, Sang-Hee;Park, Young-Deok;Oh, Choon-Suk;Ryu, Young-Kee
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.580-582
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    • 2004
  • As the demand of large and high-resolution display panels is increased, the black light units (BLU) of the display devices play an important roles. In this study we'll deal with various defects of BLUs. Patterns of defects can be classified by the scratches, the non-uniform misprinting for the diffused reflection, the surface stains, spots and etc. Due to these distorted patterns the high-resolution and high-precision could be impeded. We'll propose the visual inspection system to detect various defects by pattern-matching.

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Improved Image Matching Method Based on Affine Transformation Using Nadir and Oblique-Looking Drone Imagery

  • Jang, Hyo Seon;Kim, Sang Kyun;Lee, Ji Sang;Yoo, Su Hong;Hong, Seung Hwan;Kim, Mi Kyeong;Sohn, Hong Gyoo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.5
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    • pp.477-486
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    • 2020
  • Drone has been widely used for many applications ranging from amateur and leisure to professionals to get fast and accurate 3-D information of the surface of the interest. Most of commercial softwares developed for this purpose are performing automatic matching based on SIFT (Scale Invariant Feature Transform) or SURF (Speeded-Up Robust Features) using nadir-looking stereo image sets. Since, there are some situations where not only nadir and nadir-looking matching, but also nadir and oblique-looking matching is needed, the existing software for the latter case could not get good results. In this study, a matching experiment was performed to utilize images with differences in geometry. Nadir and oblique-looking images were acquired through drone for a total of 2 times. SIFT, SURF, which are feature point-based, and IMAS (Image Matching by Affine Simulation) matching techniques based on affine transformation were applied. The experiment was classified according to the identity of the geometry, and the presence or absence of a building was considered. Images with the same geometry could be matched through three matching techniques. However, for image sets with different geometry, only the IMAS method was successful with and without building areas. It was found that when performing matching for use of images with different geometry, the affine transformation-based matching technique should be applied.

Automatic Matching of Digital Aerial Images using LIDAR DATA (라이다데이터를 이용한 디지털항공영상의 자동정합기법)

  • Min, Seong-Hong;Yoo, Byoung-Min;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.1
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    • pp.751-760
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    • 2009
  • This research aims to develop the strategy and method to enhance the reliability of image matching results and improve the efficiency of the matching process by utilizing LIDAR data in the main image matching processes. In this work, we present the methods to utilize LIDAR data in the selection of matching entities, the search for the matched entities and the evaluation of the matching results. The proposed method has been applied to medium-resolution digital aerial images and LIDAR data acquired at the same time. The results have been analyzed in comparison with an existing method using a virtual horizontal surface rather than LIDAR DEM. This analysis indicates that the proposed method can show significantly more improved performance than the existing method. The results of this study can contribute to the improvement of the currently available commercial image matching software and the enhancement of the DEM derived from LIDAR data and matching results.

Automatic Generation of 3D Face Model from Trinocular Images (Trinocular 영상을 이용한 3D 얼굴 모델 자동 생성)

  • Yi, Kwang-Do;Ahn, Sang-Chul;Kwon, Yong-Moo;Ko, Han-Seok;Kim, Hyoung-Gon
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.7
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    • pp.104-115
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    • 1999
  • This paper proposes an efficient method for 3D modeling of a human face from trinocular images by reconstructing face surface using range data. By using a trinocular camera system, we mitigated the tradeoff between the occlusion problem and the range resolution limitation which is the critical limitation in binocular camera system. We also propose an MPC_MBS (Matching Pixel Count Multiple Baseline Stereo) area-based matching method to reduce boundary overreach phenomenon and to improve both of accuracy and precision in matching. In this method, the computing time can be reduced significantly by removing the redundancies. In the model generation sub-pixel accurate surface data are achieved by 2D interpolation of disparity values, and are sampled to make regular triangular meshes. The data size of the triangular mesh model can be controlled by merging the vertices that lie on the same plane within user defined error threshold.

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