• Title/Summary/Keyword: Area-based Matching Method

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SGM Performance Improvement of Stereo Satellite Image with Classified Image and Edge Image (분류영상과 에지영상을 이용한 입체 위성영상의 SGM 성능개선)

  • Lee, Hyoseong;Park, Byungwook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.6
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    • pp.655-661
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    • 2020
  • SGM (Semi Global Matching) can be used to find all the conjugate points between stereo images. Therefore, it enables high-density DSM (Digital Surface Model) production from high-resolution satellite images. However, water, shadows, and occlusion areas cause mismatching of the surrounding points in this method. Particularly, in buildings with large-parallax and elongated-shapes such as a Korean style apartment, it is difficult to reconstruct the 3D building even if the SGM method is applied to a high-resolution 50cm satellite image. This study proposed and performed the SGM technique with a classified image and an edge image from the IKONOS-2 satellite stereo-image with a 1m resolution to produce DSM. It was compared with the DSMs from the general SGM and the high-density ABM (Area Based Matching) matching of ERDAS software. The results of the apartment DSM by the proposed method were the best in the test area. As a result, despite the image having a resolution of 1m, the outline of the building DSM could be expressed more clearly than the existing method.

DEM Generation of Tidal Flat by the Area Based Matching Method Using Digital Aerial Stereo Images (디지털 입체 항공사진의 영역기반매칭법에 의한 갯벌 DEM 제작)

  • Lee, Hyo-Seong;Ahn, Ki-Weon;Kim, Duk-Jin
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.3
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    • pp.42-52
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    • 2010
  • The purpose of this study is to produce digital elevation model (DEM) in the Jebu tidal flat, one of the west coast of the Korean Peninsula, by means of photogrammetric techniques from aerial digital stereo-images. Produced DEM would be become the fundamental data for change detection of the sediment and erosion. To do so, epipolar line is established by relative orientation. Area-based matching is then carried out based on this line and matching size according to surface property of tidal flat after a classified image is produced from reflectance and texture of the surface. As the results, DEM generated by the proposed method showed subtle changes in height more precisely than DEM using the fixed matching size and DEM by the commercial S/W in the region, such as tidal flats having few level differences.

A Study on the Generation of Three Dimensional Orthophoto Map from Aerial Photograph by Digital Photogrammetry (수치사진측량 기법을 이용한 항공사진의 정사투영사진 지도 생성에 관한 연구)

  • 조재호;윤종성
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.16 no.2
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    • pp.203-211
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    • 1998
  • A traditional method to produce three dimensional orthophoto map has been studied by digital photogrammetry which decides a height by digitally searching conjugate points on the stereo image. Many researches in digital photogrammetric field are still in progress to determine conjugate points automatically. In this study, we analyze the effect of accuracy of area-based image matching with changing eight types of target area size using four types of image pyramid. The result of image matching to each method compared with 1/5,000 digital mapping data. We decided a optimal size of target area on a percentage of image matching. Digital elevation model is generated by matching results and bundle method. As a result, three dimensional orthophoto map is made in terms of digital elevation model and orthophoto.

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Landmark recognition in indoor environments using a neural network (신경회로망을 이용한 실내환경에서의 주행표식인식)

  • 김정호;유범재;오상록;박민용
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.306-309
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    • 1996
  • This paper presents a method of landmark recognition in indoor environments using a neural-network for an autonomous mobile robot. In order to adapt to image deformation of a landmark resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The MLTM is. used for matching an image template with deformed real images and the DASM is proposed to detect correct feature points among incorrect feature points. Finally a feed-forward neural-network using back-propagation algorithm is adopted for recognizing the landmark.

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An Efficient Approximation method of Adaptive Support-Weight Matching in Stereo Images (스테레오 영상에서의 적응적 영역 가중치 매칭의 효율적 근사화 방법)

  • Kim, Ho-Young;Lee, Seong-Won
    • Journal of Broadcast Engineering
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    • v.16 no.6
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    • pp.902-915
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    • 2011
  • Recently in the area-based stereo matching field, Adaptive Support-Weight (ASW) method that weights matching cost adaptively according to the luminance intensity and the geometric difference shows promising matching performance. However, ASW requires more computational cost than other matching algorithms do and its real-time implementation becomes impractical. By applying Integral Histogram technique after approximating to the Bilateral filter equation, the computational time of ASW can be restricted in constant time regardless of the support window size. However, Integral Histogram technique causes loss of the matching accuracy during approximation process of the original ASW equation. In this paper, we propose a novel algorithm that maintains the ASW algorithm's matching accuracy while reducing the computational costs. In the proposed algorithm, we propose Sub-Block method that groups the pixels within the support area. We also propose the method adjusting the disparity search range depending on edge information. The proposed technique reduces the calculation time efficiently while improving the matching accuracy.

Development of Image Matching Algorithm to Expand Measuring Area of Atomic Force Microscope (원자간력 현미경의 측정면적 확대를 위한 영상정합 알고리즘 개발)

  • Ko M.J;Patrangenaru V.;Hong S.W.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.568-571
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    • 2005
  • This paper introduces a correlation-based surface matching algorithm that can be used to reconstruct the surface topography of an object that is scanned from multiple overlapping regions by an AFM. The image matching technique is applied to two neighboring images intentionally overlapped with each other. To account for the inaccuracy of the coarse stage implemented in AFM, all the six axes including the rotational degrees of freedom are successively matched to maximize the correlation coefficient. The results show that the proposed 6-axes image matching method is useful for expanding the measurement range of AFM.

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A Stereo Matching Algorithm with Projective Distortion of Variable Windows (가변 윈도우의 투영왜곡을 고려한 스테레오 정합 알고리듬)

  • Kim, Gyeong-Beom;Jeong, Seong-Jong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.3
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    • pp.461-469
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    • 2001
  • Existing area-based stereo algorithms rely heavily on rectangular windows for computing correspondence. While the algorithms with the rectangular windows are efficient, they generate relatively large matching errors due to variations of disparity profiles near depth discontinuities and doesnt take into account local deformations of the windows due to projective distortion. In this paper, in order to deal with these problems, a new correlation function with 4 directional line masks, based on robust estimator, is proposed for the selection of potential matching points. These points is selected to consider depth discontinuities and reduce effects on outliers. The proposed matching method finds an arbitrarily-shaped variable window around a pixel in the 3d array which is constructed with the selected matching points. In addition, the method take into account the local deformation of the variable window with a constant disparity, and perform the estimation of sub-pixel disparities. Experiments with various synthetic images show that the proposed technique significantly reduces matching errors both in the vicinity of depth discontinuities and in continuously smooth areas, and also does not be affected drastically due to outlier and noise.

Semantic-based Mashup Platform for Contents Convergence

  • Yongju Lee;Hongzhou Duan;Yuxiang Sun
    • International journal of advanced smart convergence
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    • v.12 no.2
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    • pp.34-46
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    • 2023
  • A growing number of large scale knowledge graphs raises several issues how knowledge graph data can be organized, discovered, and integrated efficiently. We present a novel semantic-based mashup platform for contents convergence which consists of acquisition, RDF storage, ontology learning, and mashup subsystems. This platform servers a basis for developing other more sophisticated applications required in the area of knowledge big data. Moreover, this paper proposes an entity matching method using graph convolutional network techniques as a preliminary work for automatic classification and discovery on knowledge big data. Using real DBP15K and SRPRS datasets, the performance of our method is compared with some existing entity matching methods. The experimental results show that the proposed method outperforms existing methods due to its ability to increase accuracy and reduce training time.

A Variable Window Method for Three-Dimensional Structure Reconstruction in Stereo Vision (삼차원 구조 복원을 위한 스테레오 비전의 가변윈도우법)

  • 김경범
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.7
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    • pp.138-146
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    • 2003
  • A critical issue in area-based stereo matching lies in selecting a fixed rectangular window size. Previous stereo methods doesn't deal effectively with occluding boundary due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper, a variable window approach is presented to estimate accurate, detailed and smooth disparities for three-dimensional structure reconstruction. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the three-dimensional disparity space. In addition, it investigates maximum connected match candidate points and then devise the novel arbitrarily shaped variable window representative of a same disparity to treat with disparity variations of various structure shapes. We demonstrate the performance of the proposed variable window method with synthetic images, and show how our results improve on those of closely related techniques for accuracy, robustness, matching density and computing speed.

A method on Digital Elevation Model Extraction Using Satellite Images

  • Ye, Soo-Chul;Jeon, Min-Byung;Lee, Kwae-Hi
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.342-348
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    • 1998
  • The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding poults of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. In the DEM generation system, this procedure holds most of a processing time, therefore a new fast matching algorithm is proposed to reduce the time for matching. The elevation of each point is calculated using the exterior orientation obtained from modeling and disparity from matching. In this paper, the SPOT satellite images, level IA 6000 $\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM. extraction with the satellite images.

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