• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.227-228
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• 2016

Terrestrial laser scanning (TLS) technology is being applied to various fields such as the soil volume calculation and the displacement measurement of terrain, tunnels and dams. This study develops a 3D terrain processing platform for automated earth work using a terrestrial laser scanning data as the software prototype. The developed software provides cells with geo-technical information for planning work to an integrated system.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.587-590
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• 2007

The demand for more accurate and realistic 3D urban models has been increasing more and more. Many studies have been conducted to extract 3D features from remote sensing data such as satellite images, aerial photos, and airborne laser scanning data. In this paper a technique is presented to extract and reconstruct 3D buildings in urban areas using airborne laser scanning data. Firstly all points in a building were divided into some groups by height difference. From segmented laser scanning data of irregularly distributed points we generalized and regularized building boundaries which better approximate the real boundaries. Then the roof points which are subject to the same groups were classified using pre-defined models by least squares fitting. Finally all parameters of the roof surfaces were determined and 3D building models were constructed. Some buildings with complex shapes were selected to test our presented algorithms. The results showed that proposed approach has good potential for reconstructing complex buildings in detail using only airborne laser scanning data.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.447-453
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• 2007

The demand for more accurate and realistic 3D urban models has been increasing more and more. Many studies have been conducted to extract 3D features from remote sensing data such as satellite images, aerial photos, and airborne laser scanning data. In this paper a technique is presented to extract and reconstruct 3D buildings in urban areas using airborne laser scanning data. Firstly all points in a building were divided into some groups by height difference. From segmented laser scanning data of irregularly distributed points we generalized and regularized building boundaries which better approximate the real boundaries. Then the roof points which are subject to the same groups were classified using pre-defined models by least squares fitting. Finally all parameters of the roof surfaces were determined and 3D building models were constructed. Some buildings with complex shapes were selected to test our presented algorithms. The results showed that proposed approach has good potential for reconstructing complex buildings in detail using only airborne laser scanning data.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.68-82
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• 2024

The planning stage of laser scanning is crucial for acquiring high-quality 3D source data. It involves assessing the target space's environment and formulating an effective measurement strategy. However, existing practices often overlook on-site conditions, with decisions on scanner deployment and scanning locations relying heavily on the operators' experience. This approach has resulted in frequent modifications to scanning locations and diminished 3D data quality. Previous research has explored the selection of optimal scanner locations and conducted preliminary reviews through simulation, but these methods have significant drawbacks. They fail to consider scanner inaccuracies, do not support the use of multiple scanners, rely on less accurate 2D drawings, and require specialized knowledge in 3D modeling and programming. This study introduces an optimization technique for laser scanning planning using 3D simulation to address these issues. By evaluating the accuracy of scan data from various laser scanners and their positioning for scanning a retaining wall structure in a small-scale building, this method aids in refining the laser scanning plan. It enhances the decision-making process for end-users by ensuring data quality and reducing the need for plan adjustments during the planning phase.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.422-430
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• 1996

The automated scanning laser Doppler vibrometer (LDV) has been designed, and built to measure in-plane displacements associated with waves propagating on vibrating structures. Use of optical fibers allows the compact design of a laser probe head which can be scanned over the vibrating structures. An algorithm for automated self-alignment of the laser probe is developed. The system is completely automated for scanning over the structures, focusing two laser beams at each data point until the detected vibration signal is stable, and for recording and transferring the data to a system computer. The automated system allows one to get extensive data of the vibration field over the structures. The system is tested by scanning a piezoelectric cylindrical shell and a plate excited by a continuous signal and by a pulse signal, respectively. Results show that the automated scanning LDV system can be a useful tool to measure the in-plane vibration field and to detect the elastic waves propagating on the vibrating structures.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.15-26
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• 2004

The calibration for systematic error in LiDAR is crucial for the accuracy of airborne laser scanning. The main error is the misalignment of platforms between INS(Inertial Navigation System) and Laser scanner For planimetrical calibration of LiDAR, the building is good feature which has great changes in height and continuous flat area in the top. The planimetry error(pitch, roll) is corrected by adjustment of height which is calculated from comparing ground control points(GCP) of building to laser scanning data. We can know scale correction of laser range by the comparison of LiDAR data and GCP is arranged at the end of scan angle where maximize the height error. The area for scale calibration have to be large flat and have almost same elevation. At 1000m for average flying height, The Accuracy of laser scanning data using LiDAR is within 110cm in height and ${\pm}$50cm in planmetry so we can use laser scanning data for generating 3D terrain surface, expecically digital surface model(DSM) which is difficult to measure by aerial photogrammetry in forest, coast, urban area of high buildings

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.134-139
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• 2001

Laser scanners are widely used for reverse engineering and inspection of freeform parts in industry such as motors, electronic products, dies and molds. Due to the lack of measuring software and positioning device, the laser scanning processes have been erroneous and inconsistent. In order to automate measuring processes, an automated scan plan generation software and a proprietary hardware are developed. In this paper, an automated laser scanning system using a 3-axis motorized stage is proposed. In the scan planning step, scan directions, paths, and the number of scans are generated considering optical and mechanical parameters. In the scanning step, the generated scan plan is downloaded into the laser scanner and the motorized stage and the points on the surface are captured automatically. Finally, the point data set is analyzed to evaluate the performance of the system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.49-56
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• 2017

It is the approach of embedded system design that finds 3D scanning technology to analyze a real object or environment to collect data on its shape and appearance. 3D laser scanning developed during the last half of 20th century in an attempt to accurately recreate the surfaces of various objects. 1960s, early scanners used lights, cameras, and projectors to carry out the scanning in the lacks of performance which encountered many difficulties with shiny, mirroring, or transparent objects. The 3D scanning technology has leveled-up with helpful of embedded software platform research and design. In this paper, First we designed the hardware of laser/camera setup and turntable moving part which is the base of object. Second, we introduced the process of scanning 3D data with software and analyzed the resulting scanned image on the web server. Last, we made the 3D scanning embedded device with 3D printing model and experimented the 3D scanning performance with Raspberry Pi.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.379-382
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• 2007

Laser scanning technology with high positional accuracy and high density automation will be widely applied in vast range of fields including geomatics. Especially, the development of laser scanning technology enabling long range information extraction is increasing its full use in civil engineering. The purpose of this study is to extract accurate highway geometric information taking the advantages of scanning technology. Fulfilling this goal, the information of target highway's three-dimensional data was obtained through terrestrial laser scanning technology. In accordance with the result from target highway's geometric information extraction using the information above, laser scanning technology showed faster speed and better accuracy on highway geometric information extraction with reduced cost compared to traditional methods.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1137-1139
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• 2003

This paper proposed a practical method for building detection and extraction using airborne laser scanning data. The proposed method consists mainly of two processes: low and high level processes. The major distinction from the previous approaches is that we introduce a concept of pseudogrid (or binning) into raw laser scanning data to avoid the loss of information and accuracy due to interpolation as well as to define the adjacency of neighboring laser point data and to speed up the processing time. The approach begins with pseudo-grid generation, noise removal, segmentation, grouping for building detection, linearization and simplification of building boundary , and building extraction in 3D vector format. To achieve the efficient processing, each step changes the domain of input data such as point and pseudo-grid accordingly. The experimental results shows that the proposed method is promising.