• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.1
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• pp.1-9
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• 2000

In the recent day, the necessity and the effective usage are increased rapidly, and it is applied in many other fields as well as in the field of ortho-photo map. In this study, we extract each objects on the aerial image and automatically classify graphic information to produce digital map using only digital ortho-image without particular drawing devices for producing digital map. For this purpose, we have applied a lot of the image processing techniques and fuzzy theory, classified outline and lane of road and building, and had each layer according to each feature. Especially, in the case of the building, the outer vector lines extracted by pixel unit at the building were very complex, but we have developed the program to be expressed by I-dimensional linear type between building corners. In the result of this study, we could not extract and recognize all of the object on the image all together, but we have got the error within 50cm using semi-automatic technique. Therefore, this method will be used effectively in producing 1/5,000 digital map.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.979-991
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• 2016

Measuring nation images was a challenging task when employing offline surveys was the only option. It was not only prohibitively expensive, but too much time-consuming and therefore unfitted to this rapidly changing world. Although demands for monitoring real-time nation images were ever-increasing, an affordable and reliable solution to measure nation images has not been available up to this date. The researcher in this study developed a semi-automatic ontology construction algorithm, named "double-crossing double keyword collection (or DCDKC)" to measure nation images from Wikipedia in real-time. The ontology, WikiOnto, can be used to reflect dynamic image changes. In this study, an instance of WikiOnto was constructed by applying the algorithm to the big-three exporting countries in East Asia, Korea, Japan, and China. Then, the numbers of page views for words in the instance of WikiOnto were counted. A collection of the counting for each country was compared to each other to inspect the possibility to use for dynamic nation images. As for the conclusion, the result shows how the images of the three countries have changed for the period the study was performed. It confirms that DCDKC can very well be used for a real-time nation-image monitoring system.