• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.43-48
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• 2020

Open pit mines for limestone mining require rapid development of technologies and efforts to prevent safety accidents due to rapid deterioration of the slope due to deforestation and rapid changes in the topography. Accurate three-dimensional spatial information on the terrain should be the basis for reducing environmental degradation and safe development of open pit mines. Therefore, this study constructed spatial information about open pit mine using UAV(Unmanned Aerial Vehicle) and analyzed its utility. images and 3D laser scan data were acquired using UAV, and digital surface model, digital elevation model and ortho image were generated through data processing. DSM(Digital Surface Model) and ortho image were constructed using image obtained from UAV. Trees were removed using 3D laser scan data and numerical elevation models were produced. As a result of the accuracy analysis compared with the check points, the accuracy of the digital surface model and the digital elevation model was about 11cm and 8cm, respectively. The use of three-dimensional geospatial information in the mineral resource development field will greatly contribute to effective mine management and prevention of safety accidents.

• The korean journal of orthodontics
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• v.46 no.3
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• pp.129-136
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• 2016

Objective: To investigate the dimensional accuracy of digital dental models obtained from the dental cone-beam computed tomography (CBCT) scan of alginate impressions according to the time elapse when the impressions are stored under ambient conditions. Methods: Alginate impressions were obtained from 20 adults using 3 different alginate materials, 2 traditional alginate materials (Alginoplast and Cavex Impressional) and 1 extended-pour alginate material (Cavex ColorChange). The impressions were stored under ambient conditions, and scanned by CBCT immediately after the impressions were taken, and then at 1 hour intervals for 6 hours. After reconstructing three-dimensional digital dental models, the models were measured and the data were analyzed to determine dimensional changes according to the elapsed time. The changes within the measurement error were regarded as clinically acceptable in this study. Results: All measurements showed a decreasing tendency with an increase in the elapsed time after the impressions. Although the extended-pour alginate exhibited a less decreasing tendency than the other 2 materials, there were no statistically significant differences between the materials. Changes above the measurement error occurred between the time points of 3 and 4 hours after the impressions. Conclusions: The results of this study indicate that digital dental models can be obtained simply from a CBCT scan of alginate impressions without sending them to a remote laboratory. However, when the impressions are not stored under special conditions, they should be scanned immediately, or at least within 2 to 3 hours after the impressions are taken.

• Journal of the HCI Society of Korea
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• v.8 no.1
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• pp.19-28
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• 2013

As yet the use of 3D scanning technology has been limited to documentation, preservation and monitoring in cultural and natural heritage domain. Appropriate visualization of precise geometric information in scan data can support scientific interpretation of the domain experts. We studied the rendering techniques which visualize the required features from scanned models, and proposed a 3D scan data visualization pipeline, rendering methods, and a classification scheme. As a case study, we analyzed the traditional method in the study of dinosaur tracks and performed the visualization of 3D scanned models. A user test based on the result confirmed an effectiveness of the proposed method. This research showed a practical method in which 3D scanned models can be used to effective interpretation of heritage.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.347-359
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• 2010

Ortho-photos provide valuable spatial and spectral information for various Geographic Information System (GIS) and mapping applications. The absence of relief displacement and the uniform scale in ortho-photos enable interested users to measure distances, compute areas, derive geographic locations, and quantify changes. Differential rectification has traditionally been used for ortho-photo generation. However, differential rectification produces serious problems (in the form of ghost images) when dealing with large scale imagery over urban areas. To avoid these artifacts, true ortho-photo generation techniques have been devised to remove ghost images through visibility analysis and occlusion detection. So far, the Z-buffer method has been one of the most popular methods for true ortho-photo generation. However, it is quite sensitive to the relationship between the cell size of the Digital Surface Model (DSM) and the Ground Sampling Distance (GSD) of the imaging sensor. Another critical issue of true ortho-photo generation using high resolution satellite imagery is the scan line search. In other words, the perspective center corresponding to each ground point should be identified since we are dealing with a line camera. This paper introduces alternative methodology for true ortho-photo generation that circumvents the drawbacks of the Z-buffer technique and the existing scan line search methods. The experiments using real data are carried out while comparing the performance of the proposed and the existing methods through qualitative and quantitative evaluations and computational efficiency. The experimental analysis proved that the proposed method provided the best success ratio of the occlusion detection and had reasonable processing time compared to all other true ortho-photo generation methods tested in this paper.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.1-6
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• 2023

In the realm of dental prosthesis fabrication, obtaining accurate impressions has historically been a challenging and inefficient process, often hindered by hygiene concerns and patient discomfort. Addressing these limitations, Company D recently introduced a cutting-edge solution by harnessing the potential of intraoral scan images to create 3D dental models. However, the complexity of these scan images, encompassing not only teeth and gums but also the palate, tongue, and other structures, posed a new set of challenges. In response, we propose a sophisticated real-time image segmentation algorithm that selectively extracts pertinent data, specifically focusing on teeth and gums, from oral scan images obtained through Company D's oral scanner for 3D model generation. A key challenge we tackled was the detection of the intricate molar regions, common in dental imaging, which we effectively addressed through intelligent data augmentation for enhanced training. By placing significant emphasis on both accuracy and speed, critical factors for real-time intraoral scanning, our proposed algorithm demonstrated exceptional performance, boasting an impressive accuracy rate of 0.91 and an unrivaled FPS of 92.4. Compared to existing algorithms, our solution exhibited superior outcomes when integrated into Company D's oral scanner. This algorithm is scheduled for deployment and commercialization within Company D's intraoral scanner.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.244-247
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• 2005

Although several artificial disc designs have been developed for the treatment of discogenic low back pain and used clinically, biomechanical change with its implantation seldom studied. To evaluate the effect of artificial disc implantation on the biomechanics of lumbar spinal unit, nonlinear three-dimensional finite element model of L1-L5, S1 was developed and strain and stress of vertebral body and surrounding spinal ligaments were predicted. Intact osteoligamentous L1-L5, S1 model was created with 1-mm CT scan of a volunteer and known material property of each element were applied. This model also includes the effect of local muscles which was modeled with pre-strained spring elements. The intact model was validated with reported biomechanical data. Two models implanted with artificial discs, SB Charite or Prodisc, at L4/5 via anterior approach were also developed. The implanted model predictions were compared with that of intact model. Angular motion of vertebral body, force on spinal ligaments, facet joint contact force with $2\sim12$ Nm flexion-extension moment.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.11
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• pp.519-528
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• 1986

By using a least-square input estimator and likelihood ratio technique, a tracking problem is presented. A Kalman tracking filter based on constant-velocity, straight-line model is used to track a target and the filtered estimate is updated using an input estimate when a maneuver is detected. Track residuals at each scan are sensed by a detector to guard against unexpected corrections of the filter. The simulation results show there are significant improvements using the scheme presented.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.369-374
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• 2001

Gear is general mechanical elements that used for power transmission between two shafts that interval is comparatively short. and it delivers big power as accurate ratio of speed. The profile of Spur gear which is the most basic factor is divided into Trochoidal fillet curve and Involute curve. Involute curve is used a lot of a shaped curve of machine parts such as a gear, a scroll compressor and a collar of centrifugal pump. However, it is poor to study the modeling of Trochoidal fillet curve and the three dimensions model shaped mathematical curve. This paper describes a mathematical model of profile shifted involute gear. and this model is based on Camus's theory. We draw three dimensions gear have accurate mathematical function using ADS, VisualLISP. and To check accuracy and perfection, we make a program of checking Interference. and use for this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.