• Title/Summary/Keyword: 패치기반 정사영상

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Patch-Based Processing and Occlusion Area Recovery for True Orthoimage Generation (정밀정사영상 생성을 위한 패치기반 처리와 폐색지역 복원)

  • Yoo, Eun-Jin;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.83-92
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    • 2010
  • Emergence of high-resolution digital aerial cameras and airborne laser scanners have made innovative progress in photogrammetry and spatial information technology. The purpose of this study is to generate true orthoimage by recovering occlusion areas. The orthoimages were generated patch-based transformation. The occlusion areas were mutually corrected by using multiple aerial images. This study proposed a novel method of building roof based orthoimage generation and an effective method of occlusion area detection and recovery. The proposed methods could be efficient to generate true orthoimages in urban areas where occlusion areas are problematic.

Searching the Damaged Pine Trees from Wilt Disease Based on Deep Learning (딥러닝 기반 소나무 재선충 피해목 탐색)

  • ZHANGRUIRUI, ZHANGRUIRUI;YOUJIE, YOUJIE;Kim, Byoungjun;Sun, Joonam;Lee, Joonwhoan
    • Smart Media Journal
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    • v.9 no.3
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    • pp.46-51
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    • 2020
  • Pine wilt disease is one of the reasons that results in huge damage on pine trees in east Asia including Korea, Japan, and China, and early finding and removing the diseased trees is an efficient way to prevent the forest from wide spreading. This paper proposes a searching method of the damaged pine trees from wilt disease in ortho-images corrected from RGB images, which are captured by unmanned aviation vehicles. The proposed method constructs patch-based classifier using ResNet18 backbone network, classifies the RGB ortho-image patches, and make the results as a heat map. The heat map can be used to find the distribution of diseased pine trees, to show the trend of spreading disease, and to extract the RGB distribution of the diseased areas in the image. The classifier in the work shows 94.7% of accuracy.

Realtime Marker Concealment using Patch-based Texture Synthesis (패치 기반 텍스쳐 합성을 활용한 실시간 마커 은닉)

  • Yun, Kyung-Dahm;Woo, Woon-Tack
    • 한국HCI학회:학술대회논문집
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    • 2007.02a
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    • pp.96-102
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    • 2007
  • 본 논문에서는 자연스러운 증강현실 환경을 위하여 패치 기반의 텍스쳐 합성을 통한 마커 은닉 방법을 제안한다. 증강현실에서 카메라의 자세를 구하기 위한 보편적인 방법은 음영 대비가 뚜렷한 정사각형의 마커를 사용하는 것이다. 이러한 인위적인 마커의 사용은 물체의 인식과 추적을 용이하게 하지만 증강된 장면의 실감성을 감소시켜 사용성 저하를 유발하기도 한다. 제안된 마커 은닉 방법은 실시간성을 보장하면서, 배경 텍스쳐의 전역적인 특성을 유지하고, 주변 환경의 변화에 유연하다.

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Automatic Change Detection of Urban Areas using LIDAR Data (라이다데이터를 이용한 도시지역의 자동변화탐지)

  • Choi, Kyoung-Ah;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.4
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    • pp.341-350
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    • 2008
  • Change detection has been recognized as one of the most important steps to update city models. In this study, we thus propose a method to detect urban changes from two sets of LIDAR data acquired at different times. The main processes in the proposed method are (1) detecting change areas through subtraction between two DSMs generated from the LIDAR sets, (2) organizing the LIDAR points within the detected areas into surface patches, (3) classifying the class of each patch such as ground, vegetation, and building, and (4) determining the kinds of changes based on the properties and classes of the patches. The results which were obtained from the application of the proposed method to real data were verified as appropriate using the reference data manually acquired from the visual inspection of the orthoimages of the same area. The probability of success in change detection is assessed to 97% on an average. In conclusion, the proposed method is evaluated as a reliable, and efficient approach to change detection and thus the update of city model.

The Detection of Heat Emission to Solar Cell using UAV-based Thermal Infrared Sensor (UAV 기반 열적외선 센서를 이용한 태양광 셀의 발열 검출)

  • Lee, Geun Sang;Lee, Jong Jo
    • Journal of Korean Society for Geospatial Information Science
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    • v.25 no.1
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    • pp.71-78
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    • 2017
  • Many studies have been implemented to manage solar plant being supplied widely in recent years. This study analyzed heat emission of solar cell using unmanned aerial vehicle(UAV)-based thermal infrared sensor, and major conclusions are as belows. Firstly, orthomosaic image and digital surface model(DSM) data were acquired using UAV-based RGB sensor, and solar light module layer necessary to analyze the heat emission of solar cell was constructed by these data. Also as a result of horizontal error into validation points using virtual reference service(VRS) survey for evaluating the location accuracy of solar light module layer, higher location accuracy could be acquired like standard error of $dx={\pm}2.4cm$ and $dy={\pm}3.2cm$. And this study installed rubber patch to test the heat emission of solar cell and could analyzed efficiently the location of rubber patch being emitted heat using UAV-based thermal infrared sensor. Also standard error showd as ${\pm}3.5%$ in analysis between calculated cell ratio by rubber patch and analyzed cell ratio by UAV-based thermal infrared sensor. Therefore, it could be efficiently analyzed to heat emission of solar cell using UAV-based thermal infrared sensor. Also efficient maintenance of solar plant could be possible through extracting the code of solar light module being emitted of heat automatically.