• 통상정보연구
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• 제10권3호
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• pp.41-57
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• 2008

This research studies the effects of pre-show promotion, at-show promotion, and booth staff training on the image-building and relationship improvement performance of exhibitors. To this purpose, we relate each performance dimension to tactical variables such as pre show promotion, at-show promotion, and booth staff training through related literature review and conduct empirical study on their relationship. The results of this study are as follows: (1) Pre-show promotion and booth staff training have positive influence on image-building and relationship improvement performance. (2) But, at-show promotion has no effect on image-building performance, and has a negative effect on relationship improvement performance. (3) Especially, pre-show promotion has the greatest effect on relationship improvement performance, and booth staff training has the greatest effect on image-building improvement.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.238-242
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• 2007

Today's commercial high resolution satellite imagery such as that provided by IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Digital maps supply the most generally used GIS data probiding topography, road, and building information. Currently, the building information provided by digital maps is incompletely constructed for GIS applications due to planar position error and warped shape. We focus on extracting of the accurate building information including position, shape, and height to update the building information of the digital maps and GIS database. In this paper, we propose a new method of 3D building information extraction with a single high resolution satellite image and digital map. Co-registration between the QuickBird image and the 1:1,000 digital maps was carried out automatically using the RPC adjustment model and the building layer of the digital map was projected onto the image. The building roof boundaries were detected using the building layer from the digital map based on the satellite azimuth. The building shape could be modified using a snake algorithm. Then we measured the building height and traced the building bottom automatically using triangular vector structure (TVS) hypothesis. In order to evaluate the proposed method, we estimated accuracy of the extracted building information using LiDAR DSM.

• 대한원격탐사학회지
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• 제39권5_4호
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• pp.1097-1109
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• 2023

도심지는 개별 건물단위의 소규모 변화가 빈번하게 발생하는 지역이다. 기 구축된 건물 데이터베이스는 그 활용도를 높이기 위해 도심지 내의 주기적인 갱신이 요구된다. 그러나 광범위한 도심지에 대한 건물 단위 변화를 관측하기에는 자료수집의 한계가 존재한다. 따라서 본 연구에서는 넓은 범위를 단일 영상으로 촬영 가능한 위성영상을 활용하여 건물변화 탐지와 건물 정보의 갱신 가능성을 확인하고자 한다. 이를 위해 먼저 건물 데이터베이스에서 제공하는 건물 모서리점의 3차원 좌표를 이용하여 위성영상에 건물 영역을 투영한다. 투영된 건물 영역을 다시 지붕 및 전면 영역으로 구분한다. 투영된 지붕영역의 화소값을 비교하여 건물높이 갱신, 건물멸실 등 건물변화 여부를 탐지한다. 건물높이 갱신은 영상에 투영된 지붕면이 실제 영상에서 관측되는 지붕면과 일치할 때까지 높이값을 조절하여 수행된다. 영상에 투영된 모습은 나타나나 관측되는 건물이 없는 경우 철거된 건물에 해당한다. 영상에서 관측되는 건물 중에서 지붕면과 전면영역이 투영되지 않은 건물은 신축 건물에 해당된다. 이러한 변화탐지 결과를 바탕으로 건물 데이터베이스를 높이갱신, 건물삭제 및 건물생성의 세가지 분류로 갱신한다. 제안된 방식은 인천지역을 촬영한 아리랑 3A호와 인천광역시 건물 데이터베이스를 사용하여 실험하였다. 입력 단일 위성영상을 이용하여 건물변화를 탐지하고, 갱신이 필요한 건물에 대해 건물 데이터베이스 편집 작업을 수행하였다. 갱신된 건물 정보를 검증하고자 이를 이용하여 다른 아리랑 3A호 영상에 건물영역을 투영하였다. 실험결과, 갱신된 건물정보로부터 투영된 건물영역은 영상에서 관측된 건물영역과 잘 일치하였다. 이를 통해서 단일 위성영상을 이용한 건물변화탐지 및 건물 데이터베이스 갱신 가능성을 확인하였다. 후속 연구로 제안방식의 자동처리기술 개발을 수행할 예정이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.899-902
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• 2006

For a quick and accurate 3D modelling of a building, laser scanning data, digital maps, aerial photographs and satellite images should be fusioned. Moreover, library establishment according to a standard structure of a building and effective texturing method are required in order to determine the structure of a building. In this study, we made a standard library by categorizing Korean village forms and presented a model that can predict a structure of a building from a shape of the roof on an aerial photo image. We made an ortho image using the high-definition digital image and considerable amount of ground scanning point cloud and mapped this image. These methods enabled a more quick and accurate building modelling.

• 로봇학회논문지
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• 제8권2호
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• pp.82-91
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• 2013

This paper proposes a building recognition algorithm using watershed image segmentation algorithm and integrated region matching (IRM). To recognize a building, a preprocessing algorithm which is using Gaussian filter to remove noise and using canny edge extraction algorithm to extract edges is applied to input building image. First, images are segmented by watershed algorithm. Next, a region adjacency graph (RAG) based on the information of segmented regions is created. And then similar and small regions are merged. Second, a color distribution feature of each region is extracted. Finally, similar building images are obtained and ranked. The building recognition algorithm was evaluated by experiment. It is verified that the result from the proposed method is superior to color histogram matching based results.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.365-367
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• 2008

A digital city model represents a 3D environment of a city with various city object information such as 3D building model, road, and land cover. Usually, at least two satellite images with some image overlap are necessary and a complex satellite-related computation needs to be carried out to create a city model. This is an expensive technique, because it requires many resources and excessive computational cost. The authors propose a methodology to create a digital city model including 3D building model and land cover information from a single high resolution satellite image. The approach consists of image pan-sharpening, shadow recovery, building occlusion restoration, building model extraction, and land cover classification. We create a digital city model using a single KOMPSAT-2 image and review the result.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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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.

• 교육시설 논문지
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• 제19권3호
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• pp.13-20
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• 2012

In this study, we performed the psychological analysis on campus facilities for university students with the observation that the evaluation on the physical environment of the campus is related to the image evaluation of the campus users. Specifically, we investigated the cognitive structure and the image evaluation structure of users, i.e., students, on the architectural and morphological elements of campus buildings. The investigation results are summarized as follows. 1) The cognitive structure of students on the architectural and morphological elements was different from building to building. In the case of architectural elements, the campus buildings were rated high, if they were designed with emphasis on symbolic elements, while the campus buildings with simple design were rated low. However, the morphological elements exhibited the opposite results. 2) We extracted six factors by performing the factor analysis for image evaluation. From the analysis results, we found that students showed a different structure of image evaluation for each building. In addition, the image evaluation structures were found to be related with the cognitive structures on architectural and morphological elements. 3) We also performed the correlation analysis between image evaluation structure and cognitive structure on architectural and morphological aspects. The analysis results indicated that each building showed different correlation patterns. In addition, the overall image became better, as they appraised "clarity" and "uniformity" more highly.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.153-162
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• 2017

Today, weather radar is used as a key tool for modern high-tech weather observations and forecasts, along with a wide variety of ground gauges and weather satellites. In this paper, we propose a frequency transform based weather radar image processing technique to improve the weather radar image damaged by beam blocking and clutter removal in order to minimize the uncertainty of the weather radar observation. In the proposed method, DCT based mean energy correction is performed to improve damage caused by beam shielding, and DWT based morphological image processing and high frequency cancellation are performed to improve damage caused by clutter removal. Experimental results show that the application of the proposed method to the damaged original weather radar image improves the quality of weather radar image adaptively to the weather echo feature around the damaged area. In addition, radar QPE calculated from the improved weather radar image was also qualitatively confirmed to be improved by the damage. In the future, we will develop quantitative evaluation scales through continuous research and develop an improved algorithm of the proposed method through numerical comparison.

• 정보처리학회논문지B
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• 제16B권6호
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• pp.451-462
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• 2009

최근 고해상도 위성 영상의 보급에 따라 이를 활용한 서비스가 증가하고 있다. 특히, $Google\;Earth^{TM}$와 $Virtual\;Earth^{TM}$와 같은 전 지구 차원 의 3차원 가시화 서비스나 최근 일부 도시에 대하여 제공되고 있는 3차원 GIS 서비스는 지형과 지물에 대한 사실적인 기하정보를 제공하고 있다. 이러한 서비스들은 도시 개발 계획의 수립, 도로망의 개선, 엔터테인먼트 사업, 군사 시뮬레이션, 재난 및 재해 관리 등의 다양한 분야에 활용이 가능하다. 이러한 활용을 위해서는 고해상도 위성 영상을 이용하여 지형 및 지물 정보를 효과적으로 추출하는 연구가 요구된다. 본 논문 에서는 단일 위성 영상으로부터 건물의 3차원 모델을 추출하기 위한 요구사항을 살펴본 뒤 이를 기반으로 효과적인 모델 추출을 위한 시스템 을 제안한다. 제안하는 시스템은 영상의 특징 정보와 건물, 위성, 태양의 기하 관계를 이용하여 최소한의 사용자 조작으로 건물의 3차원 모델을 추출한다. 마지막으로 실제 위성 영상으로부터 건물의 3차원 모델 추출을 수행하고 효과적으로 3차원 모델을 획득할 수 있음을 보인다.