• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.69-79
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• 2020

TRecently, smart cities that solve various problems in cities based on IoT technology are in the spotlight. In particular, cases of BIM application for smooth management of construction and maintenance are increasing, and spatial information is converted into 3D data through convergence technology and used for safety diagnosis. The purpose of this study is to create and combine point clouds of a multi-story building by using a ground laser scanner and a handheld LiDAR SLAM among UAV and LiDAR equipment, supplementing the Occluded area and disadvantages of each technology, examine the effectiveness of indoor and outdoor reverse design by observing shape reproduction and accuracy. As a result of the review, it was confirmed that the coordinate accuracy of the data was improved by creating and combining the indoor and outdoor point clouds of the multi-story building using three technologies. In particular, by supplementing the shortcomings of each technology, the completeness of the shape reproduction of the building was improved, the Occluded area and boundary were clearly distinguished, and the effectiveness of reverse engineering was verified.

• The Journal of Advanced Prosthodontics
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• v.5 no.4
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• pp.452-456
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• 2013

PURPOSE. The aim of this study was to evaluate the repeatability of the digitizing of silicon rubber impressions of abutment teeth by using a white light scanner and compare differences in repeatability between different abutment teeth types. MATERIALS AND METHODS. Silicon rubber impressions of a canine, premolar, and molar tooth were each digitized 8 times using a white light scanner, and 3D surface models were created using the point clouds. The size of any discrepancy between each model and the corresponding reference tooth were measured, and the distribution of these values was analyzed by an inspection software (PowerInspect 2012, Delcamplc., Birmingham, UK). Absolute values of discrepancies were analyzed by the Kruskal-Wallis test and multiple comparisons (${\alpha}$=.05). RESULTS. The discrepancy between the impressions for the canine, premolar, and molar teeth were $6.3{\mu}m$ (95% confidence interval [CI], 5.4-7.2), $6.4{\mu}m$ (95% CI, 5.3-7.6), and $8.9{\mu}m$ (95% CI, 8.2-9.5), respectively. The discrepancy of the molar tooth impression was significantly higher than that of other tooth types. The largest variation (as mean [SD]) in discrepancies was seen in the premolar tooth impression scans: $26.7{\mu}m$ (95% CI, 19.7-33.8); followed by canine and molar teeth impressions, $16.3{\mu}m$ (95% CI, 15.3- 17.3), and $14.0{\mu}m$ (95% CI, 12.3-15.7), respectively. CONCLUSION. The repeatability of the digitizing abutment teeth's silicon rubber impressions by using a white light scanner was improved compared to that with a laser scanner, showing only a low mean discrepancy between $6.3{\mu}m$ and $8.9{\mu}m$, which was in an clinically acceptable range. Premolar impression with a long and narrow shape showed a significantly larger discrepancy than canine and molar impressions. Further work is needed to increase the digitizing performance of the white light scanner for deep and slender impressions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.2
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• pp.342-348
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• 2016

We propose an obstacle detection algorithm for unmanned ground vehicle on uneven terrain. The key ideas of the proposed algorithm are the use of two-layer laser range data to calculate the gradient of a target, which is characterized as either ground or obstacles. The proposed obstacle detection algorithm includes 4-steps: 1) Obtain the distance data for each angle from multiple lidars or a multi-layer scan lidar. 2) Calcualate the gradient for each angle of the uneven terrain. 3) Determine ground or obstacle for each angle on the basis of reference gradient. 4) Generate a new distance data for each angle for a virtual laser scanner. The proposed algorithm is verified by various experiments.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.27-29
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• 2004

This paper presents a sensor model design based on Monte Carlo Localization method. First, we define the measurement error of each sample using a map matching method by 2-D laser scanners and a pre-constructed grid-map of the environment. Second, samples are assigned probabilities due to matching errors from the gaussian probability density function considered of the sample's convergence. Simulation using real environment data shows good localization results by the designed sensor model.

• Journal of KIBIM
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• v.13 no.4
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• pp.64-73
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• 2023

This study introduces a method of estimating the 3D coordinates of structural damage from the detection results of visual inspection provided in 2D image coordinates using sensing data of UAV and 3D shape information of BIM. This estimation process takes place in a virtual space and utilizes the BIM model, so it is possible to immediately identify which member of the structure the estimated location corresponds to. Difference from conventional structural damage localization methods that require 3D scanning or additional sensor attachment, it is a method that can be applied locally and rapidly. Measurement accuracy was calculated through the distance difference between the measured position measured by TLS (Terrestrial Laser Scanner) and the estimated position calculated by the method proposed in this study, which can determine the applicability of this study and the direction of future research.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.6
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• pp.459-467
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• 2016

Using a line scan camera and a Galvano mirror, we constructed a high-speed line-scanning microscope that can generate 2D images ($8000{\times}8000pixels$) without any moving parts. The line scanner consists of a Galvano mirror and a cylindrical lens, which creates a line focus that sweeps over the sample. The measured resolutions in the x (perpendicular to line focus) and y (parallel to line focus) directions are both $2{\mu}m$, with a 2X scan lens and a 3X relay lens. This optical system is useful for measuring defects, such as spalling, chipping, delamination, etc., on the surface of carbon fiber reinforced plastic (CFRP) holes after machining in conjunction with adjustments in the angle of LED lighting. Defects on the inner wall of holes are measured by line confocal laser scanning. This confocal method will be useful for analyzing defects after CFRP machining and for fast 3D image reconstruction.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.970-976
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• 2012

In this paper, a single LRF has been used to produce a 3D map for the mobile robot navigation. The 2D laser scanners are used for mobile robots navigation, where the laser scanner is applied to detect a certain level of area by the straight beam. Therefore it is limited to the usages of 2D obstacle detection and avoidance. In this research, it is designed to complement a mobile robot system to move up and down a single LRF along the yaw axis. During the up and down motion, the 2D data are stacked and manipulated to build a 3D map. Often a single LRF data are mixed with Gaussian and impulse noises. The impulse noises are removed out by the hybrid median filter designed in this research. The 2D data which are improved by deleting the impulse noises are layered to build the 3D map. Removing impulse noises while preserving the boundary is a main advantages of the hybrid median filter which has been used widely to improve the quality of images. The effectiveness of this hybrid median filter for rejecting the impulse noises has been verified through the real experiments. The performance of the hybrid median filter is evaluated in terms of PSNR (Peak Signal to Noise Ratio) and the processing time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.247-253
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• 2019

In this paper, we present a new method for real-time tracking of human walking around a laser sensor system. The method converts range data with $r-{\theta}$ coordinates to a 2D image with x-y coordinates. Then human tracking is performed using human's features, i.e. appearances of human walking pattern, and the input range data. The laser sensor based human tracking method has the advantage of simplicity over conventional methods which extract human face in the vision data. In our method, the problem of estimating 2D positions and orientations of two walking human's ankle level is formulated based on a moving trajectory algorithm. In addition, the proposed tracking system employs a HMM to robustly track human in case of occlusions. Experimental results using a real system demonstrate usefulness of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.231-237
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• 2017

The profile of unpaved road is an important issue in the reliability of endurance test. Efforts on measuring 2D road profile and analyzing the severity have been continued in the study of performing reliable endurance test evaluations through reflecting the results of such measurement and analysis. However, 2D road profile has limitation in measuring the profile in the road width direction because data is obtained along the trailer wheel track. Therefore, in order to measure 3-dimensional shape of road surface and construct severity DB of 3D road profile, Changwon Proving Ground(CPG) of Agency for Defense Development(ADD) developed 3D profilometer which is composed of laser scanner, IMU, GPS, encoder and so on. This paper focuses on the analysis of unpaved road severity using 3D road profile for army operation roads. This results will be used to manage test courses severity of CPG.

• The korean journal of orthodontics
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• v.41 no.2
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• pp.76-86
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• 2011

Objective: To investigate whether the accuracy of 3D laser scanning is influenced by the angles and number of scans. Methods: Using a 3D laser scanner, 10 manikins with facial markers were scanned at 7 horizontal angles (front view and at $20^{\circ}$, $45^{\circ}$, and $60^{\circ}$ angles on the right and left sides). Three-dimensional facial images were reconstructed by 6 methods differing in the number and angles of scans, and measurements of these images were compared to the physical measurements from the manikins. Results: The laser scan images were magnified by 0.14 - 0.26%. For images reconstructed by merging 2 scans, excluding the front view; and by merging 3 scans, including the front view and scans obtained at $20^{\circ}$ on both sides; several measurements were significantly different than the physical measurements. However, for images reconstructed by merging 3 scans, including the front view; and 5 scans, including the front view and scans obtained at $20^{\circ}$ and $60^{\circ}$ on both sides; only 1 measurement was significantly different. Conclusions: These results suggest that the number and angle of scans influence the accuracy of 3D laser scanning. A minimum of 3 scans, including the front view and scans obtained at more than $45^{\circ}$ on both sides, should be integrated to obtain accurate 3D facial images.