• Korean Journal of Plant Resources
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• v.14 no.2
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• pp.108-115
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• 2001

For determining the effect of extracts exudated from ten industrial plant resources on germination and early growth of shoot and root of radish the allelopathic compounds screened. Germination rate and seedling growth of radish differed depending on plant species and extract concentration. Lower levels of 1% extracts exudated from industrial plant resources promoted the rate of germination of radish while higher levels of 10% extract inhibited the rate of germination. Germination rate, shoot growth and root growth of radish in higher concentration of extract also differed depending on the plant species exudated and extract concentraton of industrial plant resources. Higher concentration of extracts from Xanthium strutnarium L. Angellica gigas Nakai, and Solanum nigrum L. were completely inhibited the germination while those from Cichorium intybus L., and Polygonatum officinale Allioni were not inhibited. Extracts exudated from Xanthium strutnarium L, Angellica gigas Nakai, and Solanum nigrum L. showed the strong inhibition of shoot and root growth of radish while those from Cichorium intybus L., and Polygonatum officinale Allioni did not show the bioactivity in shoot and root growth of radish..

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.535-540
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• 2006

This paper presented an effective strategy to extract the buildings and to reconstruct 3-D buildings using high-resolution multispectral stereo satellite images. Proposed scheme contained three major steps: building enhancement and segmentation using both BDT (Background Discriminant Transformation) and ISODATA algorithm, conjugate building identification using the object matching with Hausdorff distance and color indexing, and 3-D building reconstruction using photogrammetric techniques. IKONOS multispectral stereo images were used to evaluate the scheme. As a result, the BDT technique was verified as an effective tool for enhancing building areas since BDT suppressed the dominance of background to enhance the building as a non-background. In building recognition, color information itself was not enough to identify the conjugate building pairs since most buildings are composed of similar materials such as concrete. When both Hausdorff distance for edge information and color indexing for color information were combined, most segmented buildings in the stereo images were correctly identified. Finally, 3-D building models were successfully generated using the space intersection by the forward RFM (Rational Function Model).

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.3
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• pp.76-88
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• 1999

본 논문에서는 건물이 포함된 스테레오 영상으로부터 건물을 3차원적으로 복원하기 위한 선소 특징 기반 정합 알고리듬에 대해 다루고 있다. 기존의 선소 특징 기반 정합 알고리듬은 선소 추출 기법의 성능에 많이 의존하고, 좌우 영상에서 추출된 에지 길이와 방향이 서로 차이가 날 경우 오정합이 많이 발생한다. 따라서, 건물의 형태를 올바르게 나타내지 못하는 원인이 된다. 본 논문에서는 이러한 단점을 해결하기 위하여 선소의 중심 및 양 끝점 외에 선소에 방향까지 고려하는 새로운 탐색 영역 설정 방법을 제안하였다. 또한 선소기반 정합에서 정합이 잘 이뤄지지 않는 수평선 정합 문제를 해결하기 위한 새로운 방법을 제안하였다. 한편 편평한 건물 가정 하에서 미정합된 건물 내부의 변이값을 얻기 위해 건물 추출 결과와 정합된 선소들을 이용한 보간법을 사용하였다. 제안한 알고리듬을 스테레오 항공 영상에 적용한 결과, 기존의 Hussien 등이 제안한 알고리듬에 비해 좋은 성능을 보였다.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.71-79
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• 2009

We expanded the 3D building information extraction method using shadow and vertical line from single high resolution image with meta information into the method for single high resolution image without meta information. Our method guesses an azimuth angle and an elevation angle of the sensor and the sun using reference building, selected by user, on an image. For test, we used an IKONOS image and an image extracted from the Google Earth. We calculated the Root Mean Square (RMS) error of heights extracted by our method using the building height extracted from stereo IKONOS image as reference, and the RMS error from the IKONOS image and the Google Earth image was under than 3 m. We also calculated the RMS error of horizontality position by comparison between building position extracted from only the IKONOS image and it from 1:1,000 digital map, and the result was under than 3 m. This test results showed that the height pattern of building models by our method was similar with it by the method using meta information.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.339-353
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• 2023

As the availability of high-resolution satellite imagery increases, improvement of positioning accuracy of satellite images is required. The importance of orthorectified images is also increasing, which removes relief displacement and establishes true localization of man-made structures. In this paper, we performed automated extraction of building rooftops and total building areas within original satellite images using the existing building height database. We relocated the rooftop sin their true position and generated an orthorectified building layer. The extracted total building areas were used to blank out building areas and generate true orthographic non-building layer. A final orthorectified image was provided by overlapping the building layer and non-building layer.We tested the proposed method with KOMPSAT-3 and KOMPSAT-3A satellite images and verified the results by overlapping with a digital topographical map. Test results showed that orthorectified building layers were generated with a position error of 0.4m.Through the proposed method, the feasibility of automated true orthoimage generation within dense urban areas was confirmed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.19-26
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• 2003

As recently, high-resolution satellite images of 1m spatial resolution are opened to the public and able to be used commercially, the studies that make ortho-images using them and apply to digital mapping and database of geo-spatial information system are having been progressed actively. Therefore, the purposes of this study are to establish the auto-extraction methods and to develope algorithms for automatically extracting buildings out of man-made structures, after making the IKONOS ortho-image. As the result of this study, we can extract buildings automatically at 72% out of the whole buildings. And we have analyzed the error trend by means of the comparison with ortho-image, digital map and drawing result, then we could know that obtain the good result for extraction of the building through the methods and algorithms of this study.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.43-52
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• 2009

LIDAR data, as the source of the 3D information of buildings, are used many modeling fields such as three-dimensional city models in urban planning and the visibility analysis of buildings. This study suggests a methodology, that is characterized by combining image-based and point-based process, for minimizing the user's intervention and automatically extracting building boundary only using the LIDAR data. Image processing methodology is firstly used to separate building and non-building regions from LIDAR data. Moreover, building regions are then classified main roof into remaining parts by the statistical analysis of height values, and the remaining parts are processed separately. Through the experimental results of study areas which exist many types of buildings, for example, apartment-type, stair-type, complex-type, etc. Approximately 90% building boundaries are automatically extracted by the proposed methodology.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.101-108
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• 2008

건물의 3차원 모델링은 3차원 공간정보를 구축하는데 있어서 매우 중요한 요소이다. 기존의 3차원 건물 모델링은 대부분 입체 항공사진을 이용하여 도화사에 의해 수동으로 진행되어 많은 시간과 비용이 소요된다. 이러한 한계를 극복하기 위한 방안으로 최근에는 항공라이다(LiDAR) 데이터를 이용한 모델링 방법에 대한 연구가 활발히 진행되고 있다. 기존의 항공라이다 데이터를 이용한 3차원 모델링 연구는 항공라이다 점 데이터를 보간 과정을 통하여 픽셀구조로 변환하거나 수치지도, 항공영상 등의 이종 데이터간의 융합을 통하여 건물을 모델링하는 방안 등을 제시하였다. 본 논문은 기존 건물 모델링 기법에서 사용되었던 점 데이터의 픽셀구조로의 변환 및 이종 데이터간의 융합 등의 방법을 배제하고 항공라이다 데이터만을 이용한 건물의 자동 모델링 방법을 제안하였다. 건물지붕에 대한 항공라이다 데이터를 3차원 공간상에서 재귀적으로 분할하여 패치(patch)를 구성하고, 동일한 속성을 갖는 패치들을 병합하여 건물의 구성요소를 추출한다. 추출되어진 건물의 구성요소를 대표하는 모델을 생성하여 전체적인 건물의 3차원 모델을 구성한다. 항공라이다 데이터를 이용하여 제안된 방법으로 실험한 결과, 다양한 형태의 건물 모델을 자동으로 구성할 수 있었다.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.233-239
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• 2007

현행 지적도에는 건물 위치가 표시되지 않아 지적도 활용 시 건물 위치 식별이 어렵고, 지적현황측량에 따른 비용과 시간의 소요와 불편을 격고 있으며, 지상 건물의 경계 침범으로 인한 분쟁과 소송이 일어나고 있다. 건축물 경계 추출에 관한 선행연구에서 수치정사사진과 LiDAR를 이용한 건물 경계를 추출은 원칙적으로 지적측량의 원리와 상이한 기준으로 실제 지상의 외벽 경계선이 아닌 건축물의 옥상층 경계선을 추출하였다. 따라서 본 연구에서는 건물등록을 위해 시도해 보지 않았던 건축도면을 이용하여, 기존연구에서 고려되지 못한 지붕선이나 처마선이 아닌 실제 지적측량에서 기준이 되는 외벽의 경계선을 등록하기 위해 건축도면을 활용하였으며, 등록하는 과정에서 ArcGIS 엔진을 이용하여 개발한 자동 등록 방법을 사용하였다. 지적도 필지 경계선과 건축도면의 필지 경계선을 기준으로 등록한 결과 지적현황측량 성과와 수치지역에서 연결오차로 RMSE가 0.10m, 도해지역에서 0.16m로 나타났다. 따라서 건축도면을 이용하여 지적도에 건축물의 경계를 등록함으로써 지상측량을 보완할 수 있으며, 3차원 지적구축을 위한 기반을 조성하고, 지적재조사사업에서 시간과 경비를 획기적으로 절감할 수 있을 것이다.