• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.1
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• pp.21-27
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• 2004

It will be a real good news fer the people who were lost their hometown by the construction of a large dam to be restored to the farmer state. Focused on Cheung-pyung around where most part were submerged by the Chungju large Dam founded in eurly 1980s, It used remote sensing image restoration Technique in this study in order to restore topographical features before the flood with stereo effects. We gathered comparatively good satellite photos and remotely sensed digital images, then its made a new fusion image from these various satellite images and the topographical map which had been made before the water filled by the DAM. This task was putting together two kinds of different timed images. And then, we generated DEM including the outskirts of that area as matching current contour lines with the map. That could be a perfect 3D image of test areas around before when it had been water filled by making perspective images from all directions included north, south, east and west, fer showing there in 3 dimensions. Also, for close range visiting made of flying simulation can bring to experience their real space at that time. As a result of this experimental task, it made of new fusion images and 3-D perspective images and simulation live images by remotely sensed photos and images, old paper maps about vanished submerged Dam areas and gained of possibility 3-D terrain image restoration about submerged area by large Dam construction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.475-481
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• 2019

A splint is one of assisting devices for the disabled with hemiplegia or contracture and is manually made by an experienced expert. Heated thermoplastic materials are continuously fitted to the affected part. This traditional method has a possible risk of low-temperature burn, quality variance of the splint due to the proficiency of maker. etc. While various approaches has been made using 3D printing technology in order to redeem those disadvantages, they still carry high cost issues with 3D scanners or accuracy issues with manual measurement. This research begins with symmetrical characteristics of human body and focuses on the preliminary study for the possibility of splint manufacturing with 3D printing technology based on geometric characteristics of unaffected arm. 3D right and left forearm models of healthy male adults were created by photogrammetry software and a series of digital images in order to measure the circumference and cross-sectional area of the forearm models at every 20mm from the elbow. The circumference and cross-sectional area showed tolerable levels of differences between both sides within subjects; The circumference and cross-sectional area showed very strong correlations between both sides within subjects. From these findings, the possibility of splint manufacturing with 3D printing technology could be confirmed based on the geometric characteristics of unaffected side.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.189-194
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• 2019

Forest investigation is the basic data for forest preservation and forest resource development, and periodical data acquisition and management have been performed. However, most of the current forest investigations in Korea are surveys to grasp the current status of forests, and various applications have not been made as geospatial information. In this study, the unmanned aerial scanner was used to acquire and process data in the forest area and to present an efficient forest survey method through analysis of the results. Unmanned aerial scanners can extract ground below vegetation, effectively creating DEM for forest management. It can be used as geospatial information for forest investigation and management by generating accurate topographical data that is impossible in conventional photogrammetry. It can also be used to measure distances between power lines and vegetation or manage transmission lines in forest areas. The accurate vertical distance measurement for vegetation surveys can greatly improve the accuracy of labor measurement and work efficiency compared to conventional methods. In the future, the use of unmanned aerial scanners will improve the data acquisition efficiency in forest areas, and will contribute to improved accuracy and economic feasibility compared to conventional methods.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.1
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• pp.97-108
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• 2018

The purpose of this study is to propose the construction of a visibility analysis model, which is the basis of the analysis for landscape management on the heritage sites such as historic villages and scenic sites. Results of the visibility analysis using DEM and the visibility analysis of DSM based on 3D mapping data are compared as follows: Precision level of the extracted data was confirmed to be less than 6.5cm, based on RTK survey results produced by constructing orthoimage data and DSM from the digital data of 2cm-class GSD(Ground Sample Distance) obtained by using a small UAV(Unmanned Aerial Vehicle). As a result of comparing the visibility analysis data of Digital Surface Model (DSM) using a small UAV with Digital Elevation Model(DEM) applying the height of the building to the Digital Topographic Map, it was confirmed that more realistic visibility analysis can be accomplished by applying DSM, as the structures such as fences, trees, and houses are reflected in the topographic data. The visibility analysis model using the 3D mapping technique can efficiently obtain the constantly changing topographic information when needed, by immediately constructing the data by utilizing a small UAV. It seems to be possible to propose a reasonable analysis result for preservation management such as landscape evaluation of cultural property.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.