• Journal of the Regional Association of Architectural Institute of Korea
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• v.21 no.4
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• pp.15-26
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• 2019

In recent years, researchers are increasingly trying to use BIM-based 3D models for BIM nD design such as 4D (3D + Time) and 5D (4D + Cost). However, there are still many problems in efficiently using process management based on the BIM information created at each design stage. Therefore, this study proposes a method to automate 4D and 5D design support in each design stage by using BIM-based Dynamo algorithm. To do this, I implemented an algorithm that can automatically input the process information needed for 4D and 5D by using Revit's Add-in program, Dynamo. In order to support the 4D design, the algorithm was created to enable automatic process simulation by synchronizing process simulation information (Excel file) through the Navisworks program, BIM software. The algorithm was created to automatically enable process simulation. And to support the 5D design, the algorithm was developed to enable automatic extraction of the information needed for mass production from the BIM model by utilizing the dynamo algorithm. Therefore, in order to verify the 4D and 5D design support algorithms, we verified the applicability through consultation with related workers and experts. As a result, it has been demonstrated that it is possible to manage information about process information and to quickly extract information from design and design changes. In addition, BIM data can be used to manage and input the necessary process information in 4D and 5D, which is advantageous for shortening construction time and cost. This study will make it easy to improve design quality and manage design information, and will be the foundation for future building automation research.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.119-129
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• 2010

Many algorithms for processing LIDAR data have been developed for diverse applications not limited to patch segmentation, bare-earth filtering and building extraction. However, since we cannot exactly know the true locations of individual LIDAR points, it is difficult to assess the performance of a LIDAR data processing algorithm. In this paper, we thus attempted the performance assessment of the segmentation algorithm developed by Lee (2006) using the LIDAR data generated through simulation based on sensor modelling. Consequently, based on simulation, we can perform the performance assessment of a LIDAR processing algorithm more objectively and quantitatively with an automatic procedure.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.1 s.24
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• pp.29-37
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• 2003

The High-resolution satellite images are able to get the latest information of wide range area and to shorten updating cycle of digital map better than the aerial images. Especially, as high-resolution satellite images are opened to public recently and able to be used commercially, the studies that make ortho-images using them and apply to the digital mapping and the 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 develop algorithms for automatically extracting buildings which are distributed very much in urban areas and which updating cycle needs to shorten, out of man-made structures in the IKONOS ortho-image with 1m spatial resolution. The result of this study, we can extract automatically extract 72% out of the whole buildings. And we could know that the methods and algorithms proposed in this study are good relatively analyzing the error trend by means of the comparison with ortho-image, digital map and hawing result.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.403-411
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• 2014

In this paper, an algorithm of extracting the features of home appliances and automatically building a database to identify home appliances is designed and presented. For the verification, a software library supporting this algorithm is implemented and added to an power management system server, which was already implemented to support real-time monitoring of home appliances' power consumption status and controlling their power. The implemented system consists of a system server and clients, each of which measures the power consumed by a home appliance plugged in it and transmits the information to the server in real-time over a wireless network. Through experiments, it is verified that it is possible to identify any home appliance connected to a specific client.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.111-121
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• 2006

Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.549-559
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• 2010

In geo-spatial information system building and operation, metadata is one of the crucial factors. Therefore, international and domestic organizations or associations for standardization have developed and distributed geo-based standard metadata to meet public demands. However, because metadata is composed of complicated elements and needs XML storage and management, individual organization which implement and operate practical application system is inclined to define and use its own metadata specifications. In this study, metadata extraction program, that metadata elements are directly extracted from geo-based file formats was developed to easily utilize standard metadata such as ISO/TC 19115, TTAS.KO-10.0139 and TTAS.IS-19115, and those elements are processed into XML. Furthermore, geo-based images sets are applied to another metadata of ISO/TC 19115-2. As well, metadata transformation is needed due to inconsistent or non-corresponding definition among standard metadata; in this program, transformation modules are also implemented to interoperable uses between standard metadata specifications. Widely used data formats are dealt with in this program, but extension for other formats and other metadata specifications is possible, and it is expected that availability of standard metadata is increased, through this kind of development.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.433-442
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• 2013

A set of bilingual terms is one of the most important factors in building language-related applications such as a machine translation system and a cross-lingual information system. In this paper, we introduce a new approach that automatically extracts candidates of English-Korean bilingual terms by using a bilingual parallel corpus and a basic English-Korean lexicon. This approach can be useful even though the size of the parallel corpus is small. A sentence alignment is achieved first for the document-level parallel corpus. We can align words between a pair of aligned sentences by referencing a basic bilingual lexicon. For unaligned words between a pair of aligned sentences, several assumptions are applied in order to align bilingual term candidates of two languages. A location of a sentence, a relation between words, and linguistic information between two languages are examples of the assumptions. An experimental result shows approximately 71.7% accuracy for the English-Korean bilingual term candidates which are automatically extracted from 1,000 bilingual parallel corpus.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2005.11a
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• pp.81-104
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• 2005

Accurate 3D models in urban areas are essential for a variety of applications, such as virtual visualization, CIS, and mobile communications. LiDAR(Light Detection and Ranging) is a relatively new technology for directly obtaining 3D points. Because Manual 3D data reconstruction from LiDAR data is very costly and time consuming, many researchs is focused on the automatic extraction of the useful data. In this paper, we classified ground and non-ground points data from LiDAR data by using filtering, and we reconstructed the DTM(Digital Terrain Model) using ground points data, buildings using nonground points data. After the reconstruction, we assessed the accuracy of the DTM and buildings. As a result of, DTM from LiDAR data were 0.16m and 0.59m in high raised apartments areas and low house areas respectively, and buildings were matched with the accuracy of a l/5,000 digital map.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.