• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.16 no.1
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• pp.31-49
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• 2012

In this paper, we propose a very efficient method which reconstructs the high resolution surface from a set of unorganized points. Our method is based on the level set method using adaptive octree. We start with the surface reconstruction model proposed in [20]. In [20], they introduced a very fast and efficient method which is different from the previous methods using the level set method. Most existing methods[21, 22] employed the time evolving process from an initial surface to point cloud. But in [20], they considered the surface reconstruction process as an elliptic problem in the narrow band including point cloud. So they could obtain very speedy method because they didn't have to limit the time evolution step by the finite speed of propagation. However, they implemented that model just on the uniform grid. So they still have the weakness that it needs so much memories because of being fulfilled only on the uniform grid. Their algorithm basically solves a large linear system of which size is the same as the number of the grid in a narrow band. Besides, it is not easy to make the width of band narrow enough since the decision of band width depends on the distribution of point data. After all, as far as it is implemented on the uniform grid, it is almost impossible to generate the surface on the high resolution because the memory requirement increases geometrically. We resolve it by adapting octree data structure[12, 11] to our problem and by introducing a new redistancing algorithm which is different from the existing one[19].

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.969-970
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• 2008

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.276-282
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• 2022

One of the most essential foundations upon which big institutions rely in delivering cloud computing and hosting services, as well as other kinds of multiple digital services, is the security of infrastructures for digital and information services throughout the world. Distributed denial-of-service (DDoS) assaults are one of the most common types of threats to networks and data centers. Denial of service attacks of all types operates on the premise of flooding the target with a massive volume of requests and data until it reaches a size bigger than the target's energy, at which point it collapses or goes out of service. where it takes advantage of a flaw in the Transport Control Protocol's transmitting and receiving (3-way Handshake) (TCP). The current study's major focus is on an architecture that stops DDoS attacks assaults by producing code for DDoS attacks using a cloud controller and calculating Round-Tripe Time (RTT).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.45-53
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• 2019

RGB-D SLAM (Simultaneous Localization and Mapping) refers to the technology of using deep camera as a visual sensor for SLAM. In view of the disadvantages of high cost and indefinite scale in the construction of maps for laser sensors and traditional single and binocular cameras, a method for creating three-dimensional map of indoor environment with deep environment data combined with RGB-D SLAM scheme is studied. The method uses a mobile robot system equipped with a consumer-grade RGB-D sensor (Kinect) to acquire depth data, and then creates indoor three-dimensional point cloud maps in real time through key technologies such as positioning point generation, closed-loop detection, and map construction. The actual field experiment results show that the average error of the point cloud map created by the algorithm is 0.0045m, which ensures the stability of the construction using deep data and can accurately create real-time three-dimensional maps of indoor unknown environment.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.1-10
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• 2009

Site characterization for structural stability in rock masses mainly involves the collection of joint property data, and in the current practice, much of this data is collected by hand directly at exposed slopes and outcrops. There are many issues with the collection of this data in the field, including issues of safety, slope access, field time, lack of data quantity, reusability of data and human bias. It is shown that information on joint orientation, spacing and roughness in rock masses, can be automatically extracted from LIDAR (light detection and ranging) point floods using the currently available Split-FX point cloud processing software, thereby reducing processing time, safety and human bias issues.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.368-373
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• 2003

This paper presents a cost-effective 3D foot scanner system that provides the 3-dimensional point cloud foot data to design the custom footwear. To measure the 3-dimensional point cloud data of the foot, a CCD camera, a Non-Gaussian laser line projector and optical triangulation method are employed. Furthermore, the integrated system employs a measurement base, a frame grabber, a CCD moving cart, a stepping motor and a computer. The measurement result is saved as 3D dxf format and it could be converted to 2D essential data fer a shoe design. The experimental results demonstrate that the proposed system have the decent resolution of 1mm which is enough for last and shoe design.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.83-85
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• 2017

We conducted an unbiased near- to mid-infrared imaging and spectroscopic survey of the Large Magellanic Cloud (LMC) as a part of the AKARI Mission Program "Large-area Survey of the LMC" (LSLMC, PI: T. Onaka). An area of about 10 square degrees of the LMC was observed by five photometric bands (3.2, 7, 11, 15, and $24{\mu}m$) and a low-resolution slitless prism ($2-5{\mu}m$, R ~20) equipped with AKARI /IRC. We constructed and publicly released photometric and spectroscopic catalogues of point sources in the LMC based on the survey data. The catalogues provide a large number of near-infrared spectral data, coupled with complementary broadband photometric data. Combined use of the present AKARI LSLMC catalogues with other infrared point source catalogues of the LMC possesses scientific potential that can be applied to various astronomical studies.

• Korean Journal of Computational Design and Engineering
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• v.8 no.3
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• pp.133-140
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• 2003

This paper describes a Multi-step Digitizing Method and Reverse Model generation algorithm for improvement of reverse engineering accuracy. Reverse engineering is the process of reproducing computational model by directly extracting geometric information on the physical objects. For the improvement of measuring data accuracy, we propose a multi-step digitizing method. First, measuring cloud-of-point by use of a laser scanning system. Second, gathering digitizing data by a scanning touch probe. Fine digitizing plan generated from coarse surface model directly from the cloud-of-point and it allows CMM more accurate scanning data. Finally in this paper we propose the algorithm of generating NURB surface from more accurate measuring points.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.733-734
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• 2016

This study proposes a novel approach for ground segmentation of 3D point cloud. We combine two techniques: gradient threshold segmentation, and mean height evaluation. Acquired 3D point cloud is represented as a graph data structures by exploiting the structure of 2D reference image. The ground parts nearing the position of the sensor are segmented based on gradient threshold technique. For sparse regions, we separate the ground and nonground by using a technique called mean height evaluation. The main contribution of this study is a new ground segmentation algorithm which works well with 3D point clouds from various environments. The processing time is acceptable and it allows the algorithm running in real time.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1425-1434
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• 2021

Continuous and periodic data acquisition must be preceded to maintain and manage the river facilities effectively. Adapting the existing general facilities methods, which include river surveying methods such as terrestrial laser scanners, total stations, and Global Navigation Satellite System (GNSS), has limitation in terms of its costs, manpower, and times to acquire spatial information since the river facilities are distributed across the wide and long area. On the other hand, the Mobile Mapping System (MMS) has comparative advantage in acquiring the data of river facilities since it constructs three-dimensional spatial information while moving. By using the MMS, 184,646,009 points could be attained for Anyang stream with a length of 4 kilometers only in 20 minutes. Levee points were divided at intervals of 10 meters so that about 378 levee cross sections were generated. In addition, the waterside maximum and average slope could be automatically calculated by separating slope plane form levee point cloud, and the accuracy of RMSE was confirmed by comparing with manually calculated slope. The reference slope was calculated manually by plotting point cloud of levee slope plane and selecting two points that use location information when calculating the slope. Also, as a result of comparing the water side slope with slope standard in basic river plan for Anyang stream, it is confirmed that inspecting the river facilities with the MMS point cloud is highly recommended than the existing river survey.