• Journal of the Society of Naval Architects of Korea
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• v.58 no.5
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• pp.303-313
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• 2021

Recently, quality control of the Liquefied Natural Gas Carrier (LNGC) cargo hold and block-erection interference areas using 3D scanners have been performed, focusing on large shipyards and the international association of classification societies. In this study, as a part of the research on LNGC cargo hold quality management advancement, a study on deep-learning-based scaffolding system 3D point cloud object detection and post-processing were conducted using a LNGC cargo hold 3D point cloud. The scaffolding system point cloud object detection is based on the PointNet deep learning architecture that detects objects using point clouds, achieving 70% prediction accuracy. In addition, the possibility of improving the accuracy of object detection through parameter adjustment is confirmed, and the standard of Intersection over Union (IoU), an index for determining whether the object is the same, is achieved. To avoid the manual post-processing work, the object detection architecture allows automatic task performance and can achieve stable prediction accuracy through supplementation and improvement of learning data. In the future, an improved study will be conducted on not only the flat surface of the LNGC cargo hold but also complex systems such as curved surfaces, and the results are expected to be applicable in process progress automation rate monitoring and ship quality control.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.35-41
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• 2020

3D laser scanners are an effective way to quickly acquire a large amount of data about an object. Recently, it is used in various fields such as surveying, displacement measurement, 3D data generation of objects, construction of indoor spatial information, and BIM(Building Information Model). In order to utilize the point cloud data acquired through the 3D laser scanner, it is necessary to make the data acquired from many stations through a matching process into one data with a unified coordinate system. However, analytical researches on the accuracy of point cloud data according to the registration method are insufficient. In this study, we tried to analyze the accuracy of registration method of point cloud data acquired through 3D laser scanner. The point cloud data of the study area was acquired by 3D laser scanner, the point cloud data was registered by the ICP(Iterative Closest Point) method and the shape registration method through the data processing, and the accuracy was analyzed by comparing with the total station survey results. As a result of the accuracy evaluation, the ICP and the shape registration method showed 0.002m~0.005m and 0.002m~0.009m difference with the total station performance, respectively, and each registration method showed a deviation of less than 0.01m. Each registration method showed less than 0.01m of variation in the experimental results, which satisfies the 1: 1,000 digital accuracy and it is suggested that the registration of point cloud data using ICP and shape matching can be utilized for constructing spatial information. In the future, matching of point cloud data by shape registration method will contribute to productivity improvement by reducing target installation in the process of building spatial information using 3D laser scanner.

• Journal of Sasang Constitutional Medicine
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• v.19 no.2
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• pp.22-29
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• 2007

1. Objectives Sasang Contitutional Medicine, a part of the traditional Korean medical lore, treats illness through a constitutional typing system that categorizespeople into four constitutional types. A few of the important criteria for differentiating the constitutional types are external appearances, inner state of mind, and pathological patterns. We had been developing a 3D Automatic Face Recognition Apparatus (3D-AFRA) in order to evaluate the external appearances with more objectivity. This apparatus provides a 3D image and numerical data on facial configuration, and this study aims to evaluate the mechanical accuracy of the 3D-AFRA hardware. 2. Methods Several objects of different shapes (cube, cylinder, cone, pyramid) were each scanned 10 times using the 3D Automatic Face Recognition Apparatus (3D-AFRA). The results were then compared and analyzed with data retrieved through a laser scanner known for its high accuracy. The error rates were analyzed for each grid point of facial contour scanned with Rapidform2006 (Rapidform2006 is a 3D scanning software that collects grid point data for contours of various products and products and product parts through 3D scanners and other 3D measuring devices; the grid point data thusly acquired is then used to reconstruct highly precise polygon and curvature models). 3. Results and Conclusions The average error rate was 0.22mm for the cube, 0.22mm for the cylinder, 0.125mm for the cone, and 0.172mm for the pyramid. The visual data comparing error rates for measurement figures retrieved with Rapidform2006 is shown in $Fig.3{\sim}Fig.6$. Blue tendency indicates smaller error rates, while red indicates greater error rates The protruding corners of the cube display red, indicating greater error rates. The cylinder shows greater error rates on the edges. The pyramid displays greater error rates on the base surface and around the vertex. The cone also shows greater error around the protruding edge.

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.92-100
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• 2012

A map of complex environment can be generated using a robot carrying sensors. However, representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings, posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.

• Fashion & Textile Research Journal
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• v.17 no.1
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• pp.102-115
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• 2015

Due to the diversification of lifestyles and the rapid growth of Internet environments since the 1990s, mass customization has been recently accepted as an important trend in the area of clothing and all other areas. In response to mass customized clothing products, global clothing product brands are introducing systems for mass customization such as the application of digital fashion systems that introduced IT technologies such as CAD and 3D scanners. However, studies of planning factors for clothing products applied with digital fashion systems in the area of mass production of clothing products are insufficient. Therefore, this study was intended to analyze the lifestyles of 20-30s that are expected to have the highest demand for clothing applied with digital fashion systems and present basic planning factors according to lifestyles. Through the analysis, three groups that have one of fashion pursuing type, sensory information pursuing type, and practical function pursuing type lifestyles were derived. Based on this result, consumer demand for digital fashion systems and basic factors for product planning were analyzed to present basic planning factors for digital fashion system based customized clothing by lifestyle group. This study is meaningful in that it provided basic data for product planning through digital fashion systems by analyzing the awareness, preference, necessity, and planning factors of digital fashion systems through the analysis of lifestyle types.

• 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 the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.741-747
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• 2009

For construction of 3D virtual city models, airborne digital cameras, laser scanners, multi-oblique photograph systems and other devices are currently being used. With such advanced techniques, precise 3D spatial information can be collected and high quality 3D city models can be built in a considerably large area. The 3D spatial information to be built has to provide the latest information that quickly reflects the causes of any change due to urban development. In this study, a UAV photogrammetric method using low cost UAV and digital camera was proposed to acquire and update 3D spatial information effectively on small areas where information continuously change. In the proposed UAV photogrammetric method, the elements of interior orientation were acquired through camera calibration and the vertical and oblique photographs were taken at 9 points and the 3D drawing of ground control points and buildings was performed using 20 images among the pictured images. This study also analyzed the accuracy of the proposed method comparing with ground survey data and digital map in order to examine whether the method can be used in on-demand 3D spatial information update on relatively small areas.

• 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 Society of Visualization
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• v.18 no.1
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• pp.26-37
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• 2020

Magnetic resonance thermometry (MRT) is a technique capable of measuring three-dimensional mean temperature fields by utilizing temperature-dependent shifts in proton resonance frequency. In this study, experimental verification of the technique is obtained by measuring 3D temperature fields within fully developed turbulent pipe flow, using 3T and 7T MRI scanners. The effect of the proton resonance frequency (PRF) thermal constant is examined in detail.

• Spatial Information Research
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• v.17 no.1
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• pp.39-49
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• 2009

3D terrestrial laser scanners record high precision three-dimensional coordinates of numerous points on an object surface in a short period of time, and is applied to a wide variety of fields including geodesy, and civil engineering, archaeology and architecture, and emergency service and defence, etc. However, most of terrestrial laser scanner utilized in homeland, were imported from foreign country, and also was not authorized formally as the surveying instrument. Therefore, standard test facility to calibrate and perform its evaluation in order to utilize it in a variety of fields is required. This study deals with the test facility of foreign countries for terrestrial laser scanner and suggest the establishment scheme of domestic test facility.