• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.115-119
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• 2007

종중복도 60%이상, 횡중복도 30%이상 촬영되어지는 항공영상과 스테레오 촬영이 가능한 위성영상은 도화에 사용되는 입체시를 이용하여 영상(Stereo Aerial Image) 자체를 화면상에 입체적으로 구현하여 건물의 높이 정보 판독 및 해당 지역상에서 년도별 변화지역을 판독하는 일련의 업무 수행에 있어 중요한 자료로 활용하고 있지만 장기간의 작업시간, 작업에 대한 정확성에 취약점을 나타내고 있으며, 이는 행정업무의 효율성 저하요인을 발생하고 있다. 이에 본 연구에서는 이러한 항공사진 및 위성영성의 촬영상의 특성을 활용하여 영상 매칭 DEM을 활용한 높이정보의 변화와 영상 정합을 통한 변화지역 판독을 자동화 하는 시스템을 구현하였다. 시스템 구현을 위해서 개발 언어로 Visual C++을 사용하였으며, 개발된 알고리즘에 대한 평가 수행을 위해 사용자가 직접 입체 판독 및 분석을 수행할 수 있도록 편광 모니터를 사용하여 판독 시스템을 추가적으로 개발하였다.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.3
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• pp.8-14
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• 2011

The clogging of the flow area at the tube support plates(TSPs), especially at the upper TSPs results in the water level oscillation of a steam generator during normal operation. A reduction of the TSP flow area causes to increase in pressure drop within the two-phase flow zone, which destabilizes the boiling flow through the tube bundle. This phenomenon was occasionally observed at a few domestic and foreign nuclear power plants. One of the methods for defining the flow area clogging is visual inspection, which is the most effective inspection method. The results of the visual inspection for TSPs' flow area are clogging images on TSPs' quartrefoil lobes. These images are complexly distorted due to lens aberration and external factors like the distance to a subject and angle etc. In this work, we developed the analysis algorithm for clogging image of the TSP flow area of steam generators. For this purpose, we designed an image verification device applicable to the camera employed in the field for visual inspection and then, we demonstrated the validity of image analysis algorithm by using this device and commercial autoCAD program.

• Korean Journal of Heritage: History & Science
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• v.50 no.2
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• pp.80-93
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• 2017

This study proposes a new scientific measurement method for damaged epigraph. In this new method, the Chinese characters are converted and coordinates are created for this measurement. This method is then used to decipher partially damaged characters from the parts of the coordinated characters that are damaged and intact. The Chinese characters are divided into 9 square parts by the position of their Chinese Radicals. The unknown characters are then compared and deciphered dependent upon the character shape in 9 square parts that have been created. This method is more scientific, accurate, and makes it easier to find related characters than deciphering through contexts, which is current method. When creating a new software based on this algorithm, it will be especially useful in deciphering an old manuscript or a epigraph that made ancient Chinese characters which are not currently in use. This study will also be helpful in deciphering semi-cursive styled or cursive styled epigraph, as well as semi-cursive styled or cursive styled damaged characters during follow-up research.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2002.04a
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• pp.67-75
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• 2002

Digital photogrammetry is one of the powerful tools for surveying in more perceptual ways and exploiting the continuously developing computer technology. Nowadays, digital photogrammetry is being used for a number of industrial measurements and inspections but the automation aspect of this technique is not fully developed yet. Photogrammetric work, which is obtained through usual workflow, delays for a big amount of CGP surveying, interpretation and cadastral information. Therefore through studying ways of reducing the volume of photogrammetric works, financial opportunities for digital photogrammetry can be found. This research is focused on the development of the new workflow and study algorithm in digital photogrammetry. Using this result we can reduce financial expenses and improve technologies of topographic and cadastral plans creation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.7-12
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• 2019

Clouds in the atmosphere are important variables that affect the temperature change by reflecting the radiant energy of the earth surface as well as changing the amount of sunshine by reflecting the sun's radiation energy. Especially, the amount of sunshine on the surface is very important It is essential information. Therefore, eye-observations of the sky on the surface of the earth have been enhanced by satellite photographs or relatively narrowed observation equipments. Therefore, cloud automatic observing systems have been developed in order to replace the human observers, but depending on the seasons, the reliability of observations is not high enough to be applied in the field due to pollutants or fog in the atmosphere. Therefore, we have developed a cloud observation algorithm that is robust against smog and fog. It is based on the calculation of the degree of aerosol from the all-sky image, and is added to the developed cloud reader to develop season- and climate-insensitive algorithms to improve reliability. The result compared to existing cloud readers and the result of cloud cover is improved.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.107-120
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• 2005

In Korea, MOCT and KOWACO published a standard for lineament map drawings, "The Handbook for the Drawing and Management of Hydrogeologic Map" in 2003. According to this guideline, hydrogeologic and related thematic maps should include characteristics of groundwater quality and quantity. These maps are generally drawn with ArcView GIS 3.x software. The activities of well notation on groundwater level map and Stiff diagram drawings on groundwater quality map require a great deal of efforts because hundreds or thousands of well data, water level data and hydrogeochemical data are produced through many kinds of investigations. As well, lineament density map is very important to survey and explore groundwater in a deep aquifer. In this study we developed some modules for well notation, Stiff diagram drawings, and lineament density value calculation with Avenue$^{TM}$ script and it was revealed that they can be very useful and easy for drawing groundwater thematic maps.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.267-279
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• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.