• Title/Summary/Keyword: the Building Image

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Effects of pre-show, at-show promotion and booth staff training on the image-building and relationship improvement performance of exhibitors (참가업체의 전시회 사전.현장프로모션 활동과 부스직원 교육이 기업이미지 구축 및 관계개선성과에 미치는 영향)

  • Lee, Chang-Hyun
    • International Commerce and Information Review
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    • v.10 no.3
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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.

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AUTOMATIC 3D BUILDING INFORMATION EXTRACTION FROM A SINGLE QUICKBIRD IMAGE AND DIGITAL MAPS

  • Kim, Hye-Jin;Byun, Young-Gi;Choi, Jae-Wan;Han, You-Kyung;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • 2007.10a
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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.

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Building Change Detection Methodology in Urban Area from Single Satellite Image (단일위성영상 기반 도심지 건물변화탐지 방안)

  • Seunghee Kim;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1097-1109
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    • 2023
  • Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

FUSION OF LASER SCANNING DATA, DIGITAL MAPS, AERIAL PHOTOGRAPHS AND SATELLITE IMAGES FOR BUILDING MODELLING

  • Han, Seung-Hee;Bae, Yeon-Soung;Kim, Hong-Jin;Bae, Sang-Ho
    • Proceedings of the KSRS Conference
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    • v.2
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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.

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Building Recognition using Image Segmentation and Color Features (영역분할과 컬러 특징을 이용한 건물 인식기법)

  • Heo, Jung-Hun;Lee, Min-Cheol
    • The Journal of Korea Robotics Society
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    • v.8 no.2
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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.

CREATION OF DIGITAL CITY MODEL FROM A SINGLE KOMPSAT-2 IMAGE

  • Kim, Hye-Jin;Choi, Jae-Wan;Han, You-Kyung;Kim, Yong-II
    • Proceedings of the KSRS Conference
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    • 2008.10a
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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.

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AUTOMATIC BUILDING EXTRACTION BASED ON MULTI-SOURCE DATA FUSION

  • Lu, Yi Hui;Trinder, John
    • Proceedings of the KSRS Conference
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    • 2003.11a
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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.

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A Study on the Image Evaluation of Buildings in the University Campus (대학캠퍼스 건축물에 대한 이미지평가에 관한 연구)

  • Kim, Cheon-Il;Kim, Ick-Hwan
    • Journal of the Korean Institute of Educational Facilities
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    • v.19 no.3
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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.

DCT and DWT based Damaged Weather Radar Image Retrieval (DCT 및 DWT 기반의 손상된 기상레이더 영상 복원 기법)

  • Jang, Bong-Joo;Lim, Sanghun;Kim, Won;Noh, Huiseong
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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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.

A Semi-Automatic Building Modeling System Using a Single Satellite Image (단일 위성 영상 기반의 반자동 건물 모델링 시스템)

  • Oh, Seon-Ho;Jang, Kyung-Ho;Jung, Soon-Ki
    • The KIPS Transactions:PartB
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    • v.16B no.6
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    • pp.451-462
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    • 2009
  • The spread of satellite image increases various services using it. Especially, 3D visualization services of the whole earth such as $Google\;Earth^{TM}$ and $Virtual\;Earth^{TM}$ or 3D GIS services for several cities provide realistic geometry information of buildings and terrain of wide areas. These service can be used in the various fields such as urban planning, improvement of roads, entertainment, military simulation and emergency response. The research about extracting the building and terrain information effectively from the high-resolution satellite image is required. In this paper, presents a system for effective extraction of the building model from a single high-resolution satellite image, after examine requirements for building model extraction. The proposed system utilizes geometric features of satellite image and the geometric relationship among the building, the shadow of the building, the positions of the sun and the satellite to minimize user interaction. Finally, after extracting the 3D building, the fact that effective extraction of the model from single high-resolution satellite will be show.