• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.153-156
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• 2007

There have been many studies on extracting building boundaries from LiDAR(Light Detection And Ranging) data. In such studies, points are first segmented, then are further processed to get straight boundary lines that better approximate the real boundaries. In most research in this area, processes like generalization or regularization assume that buildings have only right angles, i.e. all the line segments of the building boundaries are either parallel or perpendicular. However, this assumption is not valid for many buildings. We present a new approach consisting of three steps that is applicable to more complex building boundaries. The three steps consist of boundary tracing, generalization, and regularization. Each step contains algorithms that range from slight modifications of conventional algorithms to entirely new concepts. Four typical building shapes were selected to test the performance of out new approach and the results were compared with digital maps. The results show that the proposed approach has good potential for extracting building boundaries of various shapes.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.199-209
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• 2007

Traditionally, aerial images have been used as main sources for compiling topographic maps. In recent years, lidar data has been exploited as another type of mapping data. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. Lidar provides direct information about heights of object surfaces but have limitations with respect to boundary localization. Considering the characteristics of the sensors, this paper proposes an approach to extracting buildings from lidar and aerial imagery, which is based on the complementary characteristics of optical and range sensors. For detecting building regions, relationships among elevation contours are represented into directional graphs and searched for the contours corresponding to external boundaries of buildings. For generating building models, a wing model is proposed to assemble roof surface patches into a complete building model. Then, building models are projected and checked with features in aerial images. Experimental results show that the proposed approach provides an efficient and accurate way to extract building models.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.117-125
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• 2012

Although many studies have been conducted to extract buildings from airborne lidar data, most of them assume that all the boundaries of a building are straight line segments. This makes it difficult to model building boundaries containing curved segments correctly. This paper aims to model buildings containing curved segments as combination of straight lines and arcs. First, two sets of boundary points are extracted by adaptive convex hull algorithm and local convex hull algorithm with a larger radius. Then, arc segments are determined by average spacing of boundary points and intersection ratio of perpendicular lines. Finally, building boundary is modeled through regularization of least squares line or circle fitting. The experimental results showed that the proposed method can model the curved building boundaries as arc segments correctly by completeness of 69% and correctness of 100%. The approach will be utilized effectively to create automatically digital map that meets the conditions of the Korean digital mapping.

• Earthquakes and Structures
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• v.8 no.1
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• pp.275-304
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• 2015

The objective of this paper is to investigate the validity of transmitting boundaries in dynamic analysis of soil-structure interaction problems. As a case study, the proposed Baghdad metro line is considered. The information about the dimensions and the material properties of the concrete tunnel and surrounding soil were obtained from a previous study. A parametric study is carried out to investigate the effect of several parameters including the peak value of the horizontal component of earthquake displacement records and the frequency of the dynamic load. The computer program (Mod-MIXDYN) is used for the analysis. The numerical results are analyzed for three conditions; finite boundaries (traditional boundaries), infinite boundaries modelled by infinite elements (5-node mapped infinite element) presented by Selvadurai and Karpurapu, 1988), and infinite boundaries modelled by dashpot elements (viscous boundaries). It was found that the transmitting boundary absorbs most of the incident energy. The distinct reflections observed for the "fixed boundaries" disappear by using "transmitted boundaries". This is true for both cases of using viscous boundaries or mapped infinite elements. The type and location of the dynamic load represent two controlling factors in deciding the importance of using infinite boundaries. It was found that the results present significant differences when earthquake is applied as a base motion or a pressure load is applied at the surface ground. The peak value of the vertical displacement at nodes A, B, E and F (located at the tunnel's crown and side walls, and at the surface above the tunnel and at the surface 6.5 m away from tunnel's centre respectively) increases with the frequency of the surface pressure load for both cases 1 and 2 (traditional boundaries and mapped infinite elements respectively) while it decreases for case 3 (viscous boundaries). The modular ratio Ec/Es (modulus of elasticity of the concrete lining to that of the surrounding soil) has a considerable effect on the peak value of the horizontal displacement at node B (on the side wall of the tunnel lining) increase about (17.5) times, for the three cases (1, 2, and 3).

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.141-144
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• 2008

Many studies have been conducted on extracting buildings from ALS(Airborne Laser Scanning) data. After segmentation or classification of building points, additional steps such as generalization is required to get straight boundary lines that better approximate the real ones. In much research, orthogonal constraints are used to improve accuracies and qualities. All the lines of the building boundaries are assumed to be either parallel or perpendicular mutually. However, this assumption is not valid in many cases and more complex shapes of buildings have been increased. A new algorithm is presented that is applicable to various complex buildings. It consists of three steps of boundary tracing, grouping, and regularization. The performance of our approach was evaluated by applying the algorithm to some buildings and the results showed that our proposed method has good potential for extracting building boundaries of various shapes.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.246-251
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• 1998

This paper proposes a new building segmentation method from 1m resolution imagery using an Active Contour Model, known as "Balloons". The original balloons, which was designed by Cohen(Cohen, 1991) to extract features from medical images, are modified for building segmentation. The proposed method consists of two phases. Firstly, building boundaries are extracted by balloons with a given position on buildings from an operator. Since balloons actively adjust their shapes according to the boundaries, there is no more shape limitations on detecting buildings. Secondly, buildings are segmented by connecting the corners detected from the building boundaries, because most buildings, which are man-made objects, are effectively described by polygons. The test results show that most buildings are segmented efficiently and easily. The proposed method is new and timely as 1m resolution spaceborne imagery will be available in the very near future. The proposed method can be used fur operational building segmentation from such imagery.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.236-244
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• 2008

We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

• ETRI Journal
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• v.33 no.4
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• pp.547-557
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• 2011

This study presents an approach for extracting boundaries of various buildings, which have concave boundaries, inner yards, non-right-angled corners, and nonlinear edges. The approach comprises four steps: building point segmentation, boundary tracing, boundary grouping, and regularization. In the second and third steps, conventional algorithms are improved for more accurate boundary extraction, and in the final step, a new algorithm is presented to extract nonlinear edges. The unique characteristics of airborne light detection and ranging (LIDAR) data are considered in some steps. The performance and practicality of the presented algorithm were evaluated for buildings of various shapes, and the average omission and commission error of building polygon areas were 0.038 and 0.033, respectively.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.241-244
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• 2005

Many building detection methods mainly rely on line segments extracted from aerial or satellite imagery. Building detection methods based on line segments, however, are difficult to succeed in high resolution satellite imagery such as IKONOS imagery, for most buildings in IKONOS imagery have small size of roofs with low contrast between roof and background. In this paper, we propose an efficient method to extract line segments and group them at the same time. First, edge preserving filtering is applied to the imagery to remove the noise. Second, we segment the imagery by watershed method, which collects the pixels with similar intensities to obtain homogeneous region. The boundaries of homogeneous region are not completely coincident with roof boundaries due to low contrast in the vicinity of the roof boundaries. Finally, to resolve this problem, we set up snake model with segmented region boundaries as initial snake's positions. We used a greedy algorithm to fit a snake to roof boundary. Experimental results show our method can obtain more .correct roof boundary with small size and low contrast from IKONOS imagery. Snake algorithm, building roof detection, watershed segmentation, edge-preserving filtering

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.503-514
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• 2016

Delineation of accurate object boundaries is crucial to provide reliable spatial information products such as digital topographic maps, building models, and spatial database. In LiDAR(Light Detection and Ranging) data, real boundaries of the buildings exist somewhere between outer-most points on the roofs and the closest points to the buildings among points on the ground. In most cases, areas of the building footprints represented by LiDAR points are smaller than actual size of the buildings because LiDAR points are located inside of the physical boundaries. Therefore, building boundaries determined by points on the roofs do not coincide with the actual footprints. This paper aims to estimate accurate boundaries that are close to the physical boundaries using airborne LiDAR data. The accurate boundaries are determined from the non-gridded original LiDAR data using initial boundaries extracted from the gridded data. The similar method implemented in this paper is also found in demarcation of the maritime boundary between two territories. The proposed method consists of determining initial boundaries with segmented LiDAR data, estimating accurate boundaries, and accuracy evaluation. In addition, extremely low density data was also utilized for verifying robustness of the method. Both simulation and real LiDAR data were used to demonstrate feasibility of the method. The results show that the proposed method is effective even though further refinement and improvement process could be required.