• Title/Summary/Keyword: 건물탐지

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Improvement Method for Human Body Sensing Module and Managing System (인체 감지 센서 모듈 및 관리 시스템의 개선 방안)

  • Ahn, Tae-Won
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.10
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    • pp.223-227
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    • 2014
  • This paper presents an improvement method for human body sensing module and management system, specifically focused on the human body detection module with ultrasonic sensors to detect the usage of toilets and the management system to control the state of the toilets of the entire building. The proposed human body sensing module consists of the detection sensor to detect the movement of human body and the contact sensor to detect the position in a certain distance. The management system is configured of the control unit to process the signal transmitted from sensors, opening and closing valves according to the sensing signal, and the short range wireless communication unit to save the operational status data as well as transmit the data at regular intervals.

A Study on True Ortho-photo Generation Using Epipolar Geometry and Classification Algorithm (에피폴라 기하와 군집화 알고리즘을 이용한 정밀 정사투영영상 제작에 관한 연구)

  • Oh, Kum-Hui;Hwang, Hyun-Deok;Kim, Jun-Chul;Shin, Sung-Woong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.6
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    • pp.633-641
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    • 2008
  • This study introduces the method of detecting and restoring occlusion areas by using epipolar algorithm and K-means classification algorithm for true ortho-photo generation. In the past, the techniques of detecting occlusion areas are using the reference images or information of buildings. But, in this study the occlusion areas can be automatically detected by using DTM data and exterior orientation parameters. The detected occlusion areas can be restored by using anther images or the computed values which are determined in K-means classification algorithm. In addition, this method takes advantages of applying epipolar algorithm in order to find same location in overlapping areas among images.

Refinement of Building Boundary using Airborne LiDAR and Airphoto (항공 LiDAR와 항공사진을 이용한 건물 경계 정교화)

  • Kim, Hyung-Tae;Han, Dong-Yeob
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.3
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    • pp.136-150
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    • 2008
  • Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

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Automatic Co-registration of Existing Building Models and Digital Image (건물 모델과 디지털 영상간의 자동정합 방법)

  • Jung, Jae-Wook;Sohn, Gun-Ho;Armenakis, Costas
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.125-132
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    • 2010
  • With recent advancement of remote sensing technology, a variety of data acquisition over the same area is achievable. An automated co-registration of heterogeneous airborne images is a critical step for change detection. This paper describes an automatic method for co-registration between digital image and existing building model. Optimal building models for co-registration purpose are extracted as primitives from existing building model database. A set of homologous features between straight lines extracted from aerial digital image and model primitive are computed based on geometric similarity function. With obtained homologous features, EO parameter is recomputed using least square method. The result shows that die suggested method automatically co-register two data set in a reliable manner.

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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Improvement of Building Region Correspondence between SLI and Vector Map Based on Region Splitting (영역분할에 의한 SLI와 벡터 지도 간의 건물영역 일치도 향상)

  • Lee, Jeong Ho;Ga, Chill O;Kim, Yong Il;Yu, Ki Yun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.4
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    • pp.405-412
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    • 2012
  • After the spatial discrepancy between SLI(Street-Level Imagery) and vector map is removed by their conflation, the corresponding building regions can be found based on SLI parameters. The building region correspondence, however, is not perfect even after the conflation. This paper aims to improve the correspondence of building regions by region splitting of an SLI. Regions are initialized by the seed lines, projection of building objects onto SLI scene. First, sky images are generated by filtering, segmentation, and sky region detection. Candidates for split lines are detected by edge detector, and then images are splitted into building regions by optimal split lines based on color difference and sky existence. The experiments demonstrated that the proposed region splitting method had improved the accuracy of building region correspondence from 83.3% to 89.7%. The result can be utilized effectively for enhancement of SLI services.

Extraction and Modeling of Curved Building Boundaries from Airborne Lidar Data (항공라이다 데이터의 건물 곡선경계 추출 및 모델링)

  • Lee, Jeong Ho;Kim, Yong Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.4
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    • pp.117-125
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    • 2012
  • Although many studies have been conducted to extract buildings from airborne lidar data, most of them assume that all the boundaries of a building are straight line segments. This makes it difficult to model building boundaries containing curved segments correctly. This paper aims to model buildings containing curved segments as combination of straight lines and arcs. First, two sets of boundary points are extracted by adaptive convex hull algorithm and local convex hull algorithm with a larger radius. Then, arc segments are determined by average spacing of boundary points and intersection ratio of perpendicular lines. Finally, building boundary is modeled through regularization of least squares line or circle fitting. The experimental results showed that the proposed method can model the curved building boundaries as arc segments correctly by completeness of 69% and correctness of 100%. The approach will be utilized effectively to create automatically digital map that meets the conditions of the Korean digital mapping.

Object-based classification for building detection using VHR image and Lidar data (고해상도 영상 및 라이다 자료를 이용한 객체 기반 건물 탐지)

  • Yoon Yeo-Sang
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.307-310
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    • 2006
  • 고해상도(VHR, Very High Resolution) 영상은 활용에 따라 도심의 다양한 정보를 얻을 수 있는 잠재적 가치가 매우 큰 자료이다. 그러나 이러한 고해상도 영상자료는 매우 높은 공간해상력으로 인해 같은 용도의 객체 혹은 같은 객체(예, 건물)라 할지라도 다양한 분광 특성 및 형태로 표현된다. 그러므로 이러한 고해상도영상을 이용하여 효과적으로 주제도를 생성하기 위해서는 현재까지 영상분류 분야에서 주로 활용되고 있는 화소(pixel)단위 기반의 분석방법으로는 한계가 존재한다. 본 연구에서는 이러한 문제점을 보완하기 위한 방법으로 활발한 연구가 진행되고 있는 세그멘트(segment) 혹은 객체(object) 기반 분류기법을 고해상도 영상 및 라이다 자료에 적용하여 도심지역의 건물들을 추출해 보았으며, 그 활용 가능성에 대하여 판단해 보았다. 이러한 세그멘트 기법은 분류하고자 하는 객체들을 하나의 동일한 특성을 가지는 집단으로 모으는 방법을 말하는데, 이를 위해 본 연구에서는 multi-resolution image segmentation기법을 제공해주는 eCognition이라는 소프트웨어를 이용하였다.

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Development of Automatic Operating System for Exit Door using RF (무선을 이용한 비상문 자동개폐 시스템 개발)

  • Lim Youn-Sub;Hwang Byung-Kon
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.1
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    • pp.7-12
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    • 2006
  • In this paper, we develop a control system with fire receiver and emergency light that controls (manages) emergency door by wireless signals which prevents crime but also helps evacuate in (fire) emergency. This automatic door operator can be installed on any buildings which have a problem of opening or shutting emergency doors, and it is especially good for buildings with high fire vulnerabilities such as complex buildings, apartments and multistoried buildings without easy control of rooftop doors.

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Building Boundary Reconstruction from Airborne Lidar Data by Adaptive Convex Hull Algorithm (적응적 컨벡스헐 알고리즘을 이용한 항공라이다 데이터의 건물 경계 재구성)

  • Lee, Jeong-Ho;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.3
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    • pp.305-312
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    • 2012
  • This paper aims at improving the accuracy and computational efficiency in reconstructing building boundaries from airborne Lidar points. We proposed an adaptive convex hull algorithm, which is a modified version of local convex hull algorithm in three ways. The candidate points for boundary are first selected to improve efficiency depending on their local density. Second, a searching-space is adjusted adaptively, based on raw data structure, to extract boundary points more robustly. Third, distance between two points and their IDs are utilized in detecting the seed points of inner boundary to distinguish between inner yards and inner holes due to errors or occlusions. The practicability of the approach were evaluated on two urban areas where various buildings exist. The proposed method showed less shape-dissimilarity(8.5%) and proved to be two times more efficient than the other method.