• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.39-48
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• 2012

Filtering process that separates ground and non-ground points from LIDAR data is important in order to create the digital elevation model (DEM) or extract objects on the ground. The purpose of this research is to select the most effective filtering algorithm through qualitative and quantitative analysis for the existing filtering method used to extract ground points from LIDAR data. For this, four filtering methods including Adaptive TIN(ATIN), Perspective Center-based filtering method(PC), Elevation Threshold with Expand Window(ETEW) and Progressive Morphology(PM) were applied to mountain area, urban area and the area where building and mountains exist together. Then the characteristics for each method were analyzed. For the qualitative comparison of four filtering methods used for the research, visual method was applied after creating shaded relief image. For the quantitative comparison, an absolute comparison was conducted by using control points observed by GPS and a relative comparison was conducted by the digital elevation model of the National Geographic Information Institute. Through the filtering experiment of the LIDAR data, the Adaptive TIN algorithm extracted the ground points in mountain area and urban area most effectively. In the area where buildings and mountains coexist, progressive morphology algorithm generated the best result. In addition, as a result of qualitative and quantitative comparisons, the applicable filtering algorithm regardless of topographic characteristics appeared to be ATIN algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.529-538
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• 2012

By using an algorithm derived by a multiple linear regression analysis, a technique for filtering was developed; and by using the developed technique, the results of conducting filtering of the raw data collected via scanning with a terrestrial LiDAR the actual sloped terrain was analyzed. As such, when filtering was applied by dividing the observation areas into two areas with the topographical line as a reference in order to improve the filtering accuracy, it was seen that the filtering accuracy improved by about 8.73% as compared to when filtering was applied without dividing the observation area. In addition, considering the fact that the accuracy improved by 5~7% when the sloped sides of a multicurvature topography were divided and a complex filtering applied as compared to when filtering was applied for the entire area or by regions, it can be asserted that the accuracy was higher when a complex filtering was conducted by dividing the sloped areas where the slope is not constant due to the multi-curvature of topography.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.641-650
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• 2011

Airborne LIDAR system, utilized in various forest studies, provides efficiently spatial information about vertical structures of forest areas. The tree height is one of the most essential measurements to derive forest information such as biomass, which can be estimated from the forest terrain model. As the terrain model is generated by the interpolation of ground points extracted from LIDAR data, filtering methods with high reliability to classify reliably the ground points are required. In this paper, we applied three representative filtering methods to forest LIDAR data with diverse characteristics, measured the errors and performance of these methods, and analyzed the causes of the errors. Based on their complementary characteristics derived from the analysis results, we have attempted to combine the results and checked the performance improvement. In most test areas, the convergence method showed the satisfactory results, where the filtering performance were improved more than 10% in maximum. Also, we have generated DTM using the classified ground points and compared with the verification data. The DTM retains about 17cm RMSE, which can be sufficiently utilized for the derivation of forest information.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.471-475
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• 2004

LiDAR의 표고점 데이터에서 건물, 수목 등과 같이 주위보다 높은 고도 값을 가지는 대상물을 제거하여 DEM을 생성하기 위한 여러 가지 필터링 기법들이 개발되고 있으며 대표적인 필터링 방법으로는 분산을 이용한 linear prediction 기법, 주변 점들과의 경사관계를 이용한 slope-based 기법, morphology 필터, dual rank 필터 등이 있다. 이러한 기법들은 커널(kernel)의 크기를 대상 지역에 맞도록 사용자가 직접 지정해주어야 하고, 건물의 크기가 다양한 지역에 적용하기 위해서는 가변 크기(variable size)의 커널을 필요로 한다. 본 연구에서는 다양한 크기의 건물이 존재하는 지역에 대하여 커널의 크기를 변화시키지 않고 필터링을 수행하는 새로운 커널 연산 기법을 제안하였다. 또한 기존 필터링 기법에서는 커널에 의해 갱신된 연산값이 다음 연산에 반영되지 않으나 본 연구에서는 갱신된 값이 바로 다음 연산에 반영되도록 하였다. 건물과 수목 등을 제거하기 위하여 주변 화소와의 높이 차를 이용하였으며 대상물이 제거된 부분은 주변 화소를 이용하여 보간하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.55-62
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• 2007

Recent advances in airborne LiDAR technology allow rapid and inexpensive measurements of topography over large areas. The generation of DTM/DEM is essential to numerous applications such as the fields of civil engineering, environment, city planning and flood modeling. The demand for LiDAR data is increasing due to the reduced cost for DTM generation and the increased reliability, precision and completeness. In order to generate DTM, measurements from non-ground features such as building and vegetation have to be classified and removed. In this paper, a segmented morphology filter was developed to detect non-ground LiDAR measurements. First, segments LiDAR point clouds based on the elevation. Secondly classifies those protruding segments into non-ground points. Those non-ground points such as building and vegetation are removed, while ground points are preserved for DTM generation. For experiments, data sets used in Comparison of Filters (ISPRS, 2003) depicting urban and rural areas were selected. The experimental results show that the proposed filter can remove most of the non-ground points effectively with less commission and omission errors.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.79-86
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• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.469-476
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• 2009

The new laser scanning technology allows to attain 3D information faster with higher accuracy on surface ground, vegetation and buildings of the earth surface. This acquired information can be used in many areas after modifying them appropriately by users. The contour production for accurate landform is an advanced technology that can reveal the mountain area landscapes hidden by the trees in detail. However, if extremely precise LiDAR data is used in constructing the contour, massive-sized data intricates the contour diagram and could amplify the data size inefficiently. This study illustrates the algorithm producing contour that is filtered in stages for more efficient utilization using the LiDAR contour produced by the detailed landscape data. This filtering stages allow to preserve the original landscape shape and to keep the data size small. Point Filtering determines the produced contour diagram shape and could minimize data size. Thus, in this study we compared experimentally filtered contour with the current digital map(1:5,000).

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.21-25
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• 2008

최근 측량기술이 발전함에 따라 다양한 지형공간정보를 획득할 수 있게 되었다. 특히 레이저스캐닝 기술의 도입은 정밀한 지형과 식생 및 인공지물 등에 대한 정보를 신속하게 획득하여 원하는 최신 정보를 가공할 수 있게 되었다. 본 연구에서는 라이다의 식생 데이터에서 점의 밀도 분포를 통하여 정량적인 식생분포 분석을 실시하였다. 또한, 정밀한 지형 모델에 대하여 생성되는 라이다 등고선의 효율적인 활용을 위하여 단계별로 필터링을 실시하여 정확성은 유지하면서 저용량의 등고선을 생성하고 도로 및 엔지니어링 분야 활용을 높일 수 있도록 하였다. 이러한 지능적이고 과학적인 연구는 국내 라이다데이터의 적극적인 활용성을 높이고 누구나 쉽게 사용할 수 있도록 하는데 목적이 있으며, 건설 분야뿐만 아니라 생태지도 및 주제도, 재해 환경 분야, 홍수지도, 도시모델링 등 다양한 분야의 활용성을 가능하도록 한다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.253-256
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• 2001

본 논문에서는 전처리 과정에서 잡음의 효과적 처리를 위해 기존의 필터 방식들이 가지는 단점인 경계 부분의 블러링 현상을 줄이고 정확한 에지 위치를 보존할 수 있는 비등방성 확산 필터를 사용하여 CT나 MRI 2차원 영상 슬라이스들을 만들어내고 이 슬라이스들을 3차원 데이터 셋으로 구성하여 3차원 공간의 볼륨 데이터로 시각적인 영상정보를 얻는데 있다.

• The Journal of the Korea Contents Association
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• v.7 no.8
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• pp.50-58
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• 2007

We design a filtering management scheme with synchronization function under a realtime RFID middleware system for larger-scale data processing. The application interface(AI) is to support a various access protocol, HTTP, XML, JMS, and SOAP for the RFID applications. Generally, the synchronization problem is occurred in multiple accessing of clients for single filtering file. In this paper, we implement a filtering management scheme supporting the synchronization using the filter management process, and then demonstrate the RFID middleware filtering scheme.