• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.43-52
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• 2009

LIDAR data, as the source of the 3D information of buildings, are used many modeling fields such as three-dimensional city models in urban planning and the visibility analysis of buildings. This study suggests a methodology, that is characterized by combining image-based and point-based process, for minimizing the user's intervention and automatically extracting building boundary only using the LIDAR data. Image processing methodology is firstly used to separate building and non-building regions from LIDAR data. Moreover, building regions are then classified main roof into remaining parts by the statistical analysis of height values, and the remaining parts are processed separately. Through the experimental results of study areas which exist many types of buildings, for example, apartment-type, stair-type, complex-type, etc. Approximately 90% building boundaries are automatically extracted by the proposed methodology.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.27-34
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• 2013

Due to the increased interest in global warming, interest in forest resources aimed towards reducing greenhouse gases have subsequently increased. Thus far, data related to forest resources have been obtained, through the employment of aerial photographs or satellite images, by means of plotting. However, the use of imaging data is disadvantageous; merely, due to the fact that recorded measurements such as the height of trees, in dense forest areas, lack accuracy. Within such context, the authors of this study have presented a method of data processing in which an individual tree is isolated within forested areas through the use of LIDAR data and ortho-images. Such isolation resulted in the provision of more efficient and accurate data in regards to the height of trees. As for the data processing of LIDAR, the authors have generated a normalized digital surface model to extract tree points via local maxima filtering, and have additionally, with motives to extract forest areas, applied object oriented image classifications to the processing of data using ortho-images. The final tree point was then given a figure derived from the combination of LIDAR and ortho-images results. Based from an experiment conducted in the Yongin area, the authors have analyzed the merits and demerits of methods that either employ LIDAR data or ortho-images and have thereby obtained information of individual trees within forested areas by combining the two data; thus verifying the efficiency of the above presented method.

• Proceedings of the Optical Society of Korea Conference
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• 1998.08a
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• pp.210-211
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• 1998

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.43-54
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• 2012

This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.491-500
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• 2004

As the applications of 3D GIS rapidly increase, the need for acquisition and continuos update of urban models is increasingly emphasized. Particularly, building models has been considered as the most crucial component of urban models. Many researchers thus have focused on building extraction from mainly aerial photos or airborne LIDAR data but so far mostly failed to achieve satisfactory results in terms of both completeness and precision because of the intrinsic limitation of the sensory data themselves. Therefore, instead of the airborne sensors, we utilize a terrestrial LIDAR to generate precise and complete building models. This paper presents the overview of the sensors for data acquisition, describes data processing methods for building modelling from the acquired data and summerizes the experimental results.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.945-948
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• 2020

최근 코로나 사태로 인하여 한국에서는 사람 간에 거리를 두는 사회적 거리 두기와 생활 속 거리두기를 시행하고 있다. 또 식당에서의 지출 중 가장 큰 비율을 차지하고 있다. 인건비를 절감하기 위해 본 연구는 2D Lidar 센서를 사용하여 식당에서의 사람과의 접촉이 가장 큰 서빙의 역할을 로봇이 직접 하는 것을 목표로 하였다. Lidar 센서를 이용해서 SLAM을 구현하였고 안드로이드 앱을 사용하여 주문 결제를, Four Bar Linkage를 사용하여 음식 전달 부분을 구현하였다.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.52-63
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• 2009

This is a study on large-scale rock joint roughness measurements using LIDAR (light detection and ranging) and the Split-FX point cloud processing software. The large-scale rock Joint Roughness Coefficient (JRC) is calculated using the maximum amplitude of joint asperities over the profile length on large-scale Joint surfaces of rock. As the profile length increases, JRC decreases due to scale-effects of rock specimens and is non-stationary. Also JRC shows anisotropy depending on the profile direction. The profile direction is measured relative to either dip or strike of the large-scale joint.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.93-97
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• 2024

With the development of promising future mobility and urban air mobility (UAM) technologies, the demand for LIDAR sensors has increased. The SWIR photodetector is a sensor that detects lasers for the 3D mapping of lidar sensor and is the most important technology of LIDAR sensor. An SWIR photodetector based on QDs in an eye-safe wavelength band of over 1400 nm has been reported. QDs-based SWIR photodetectors can be synthesized and processed through a solution process and have the advantages of low cost and simple processing. However, the organic ligands of QDs have insulating properties that limit their ability to improve the sensitivity and stability of photodetectors. Therefore, the technology to replace organic ligands with inorganic ligands must be developed. In this study, the organic ligand of the synthesized PbS QDs was replaced with a MAPI inorganic ligand, and an SWIR photodetector was fabricated. The analysis of the characteristics of the manufactured photodetector confirmed that the photodetector based on MAPI-capped PbS QDs exhibited up to 26.5% higher responsivity than that based on organic ligand PbS QDs.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.11-20
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• 2010

In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.