• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.49-56
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• 2020

Detecting shadows in images and restoring or removing them was a very challenging task in computer vision. Traditional researches used color information, edges, and thresholds to detect shadows, but there were errors such as not considering the penumbra area of shadow or even detecting a black area that is not a shadow. Deep learning has been successful in various fields of computer vision, and research on applying deep learning has started in the field of shadow detection and removal. However, it was very difficult and time-consuming to collect data for network learning, and there were many limited conditions for shooting. In particular, it was more difficult to obtain shadow data from buildings and satellite images, which hindered the progress of the research. In this paper, we propose a method for generating shadow data from buildings and satellites using Unity3D. In the virtual Unity space, 3D objects existing in the real world were placed, and shadows were generated using lights effects to shoot. Through this, it is possible to get all three types of images (shadow-free, shadow image, shadow mask) necessary for shadow detection and removal when training deep learning networks. The method proposed in this paper contributes to helping the progress of the research by providing big data in the field of building or satellite shadow detection and removal research, which is difficult for learning deep learning networks due to the absence of data. And this can be a suboptimal method. We believe that we have contributed in that we can apply virtual data to test deep learning networks before applying real data.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.211-219
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• 2007

Building extraction is one of the essential issues for 3D city modelling. In recent years, high-resolution satellite imagery has become widely available and it brings new methodology for urban mapping. In this paper, we have developed a semi-automatic algorithm to determine building heights from monoscopic high-resolution satellite data. The algorithm is based on the analysis of the projected shadow and actual shadow of a building. Once two roof comer points are measured manually, the algorithm detects (rectangular) roof boundary automatically. Then it estimates a building height automatically by projecting building shadow onto the image for a given building height, counting overlapping pixels between the projected shadow and actual shadow, and finding the height that maximizes the number of overlapping pixels. Once the height and roof boundary are available, the footprint and a 3D wireframe model of a building can be determined. The proposed algorithm is tested with IKONOS images over Deajeon city and the result is compared with the building height determined by stereo analysis. The accuracy of building height extraction is examined using standard error of estimate.

• Tunnel and Underground Space
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• v.3 no.2
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• pp.109-117
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• 1993

The existence and exact location of cavity is very important for the stability of the large underground storage house or building. Numerical method such as finite element method and finite diference methods are widely used because of model's complexity. Preliminary tests such as calculation step test, mesh size test and model size test were tried. Upper shadow zone and lower shadow zone can be calculated from 50% amplitude level of measuring data. From these statistical methods, the calculatied position of cavity coincided nearly with actual position of model testing cavity.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.179-189
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• 2009

We present a novel shadow culling algorithm for interactive ray tracing. Our approach exploits frame-to-frame coherence instead of preprocessing of building shadow data, so this algorithm is suitable for dynamic ray raying. In this algorithm, shadow processing results are stored to each primitive and used in the next frames. We also present a novel occlusion testing method. This method corrects potential shadow errors in our culling algorithm and requires low overhead. Experiment results show that our algorithm reduced both the traversal cost by 7-19 percent and the intersection cost by 9-24 percent.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.738-748
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• 2010

In order to clarify the impact of variation of albedo on the atmospheric boundary layer caused by the density of building in urban areas, both satellite data analysis and numerical experiments were carried out. Utilized satellite data were multi-spectral visible data detected by the Korea Multi- Purpose Satellite -2 (KOMSAT-2), and the numerical models for the estimation of surface heat budget are Albedo Calculation Model (ACM) and Oregon State University Planetary Boundary Layer model (OSUPBL). In satellite data analysis, the estimated albedo in densely populated building area is lower than other regions by 17% at the maximum due to the shadow effect of skyscraper buildings. The surface temperature reached $43.5^{\circ}C$ in the highly dense and tall building area and $37.4^{\circ}C$ in the coarse density area of low buildings, respectively. However, the low albedo in densely integrated building area is not directly related to the increase of surface air temperature since the mechanical turbulence induced by the roughness of buildings is more critical in its impact than the decrease of albedo.

• Journal of the Korean housing association
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• v.17 no.5
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• pp.39-46
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• 2006

This study was conducted in seven metropolitan cities in south korea containing Seoul and Busan etc and used DevC++ language program in the process to get datas of the distance ratio between apartment houses by the length of time accepting sunshine during the day time. Basically by inputting information such as a certain date, longitude, latitude etc, it was possible to get outputs of the length of shadow. This study obtained the data from the model experiment and computer programs which analysis of the sunshine environment. As mentioned above, by analysing relations between sunshine-ralated laws in each cities and those influential factors, it is possible to suggest the fundamental data of distance ratio between apartment houses when designing a new building with more optimized way.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.556-563
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• 2020

Most of a BIPVS (Building Integrated Photovoltaic System) is installed on the rooftop or wall of a building. Therefore, the main factor to consider for selecting the installation site is the shadow effects produced by the surrounding buildings. On the other hand, when the photovoltaic was installed on soundproof walls, shadow effects were produced by not only surrounding buildings but also the surrounding trees. Therefore, a different data model and algorithm with the BIPVS case are essential for proper installation sites selection of a SIPVS (Soundproof wall Integrated Photovoltaic System). This paper deals with the DSM (Digital Surface Model)-based proper installation site analysis for SIPVS. First, the solar incident and altitude angles of the installation candidate sites (solar panel) during the year were calculated. Second, the shadow effects (shadowed or unshadowed) were determined for the candidate sites at each time with the DSM. Third, the amount of solar radiation was calculated with the incident angle for the candidate sites at an unshadowed period. The proper installation site of the SIPVS could then be selected by comparing the accumulated annual solar radiation for each candidate. The proposed algorithm was implemented as a prototype (Java program). From the experiment, the order of the installation suitability was determined among the nine candidates. The proposed algorithm could be used for proper BIPVS installation site analysis aimed at the lower part of a building and calculation of the expected power production.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.47-56
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• 2010

The use of airborne LiDAR data obtained by airborne laser scanners has increased in the field of spatial information such as building modeling. LiDAR data consist of irregularly distributed 3D coordinates and lack visual and semantic information. Therefore, LiDAR data processing is complicate. This study suggested a method of LiDAR data segmentation using roof surface patches from aerial images. Each segmented patch was modeled by analyzing geometric characteristics of the LiDAR data. The optimal functions could be determined with segmented data that fits various shapes of the roof surfaces as flat and slanted planes, dome and arch types. However, satisfiable segmentation results were not obtained occasionally due to shadow and tonal variation on the images. Therefore, methods to remove unnecessary edges result in incorrect segmentation are required.

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.331-336
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• 2015

In this study, a numerical model developed for sunshine duration based on GIS data was used. This model considers blocking caused by topography and buildings and it is properly applicable to evaluation of sunshine duration environment in urban areas. The model reasonably well predicted the solar altitude and azimuth angels, compared to those provided by Korea Astronomy and Space Science Institute (KASI). The developed model was applied to evaluation of sunshine duration environment around the Seonleung Park located near a building-congested area in Seoul. The model well reproduced shadow caused by buildings and/or topography in the numerical domain at 09:00 on August 1, 2015. In addition, the model was applied to finding a suitable measurement sites for pyrheliometer around the Seonleung Park. The model was also usefully applied to finding a suitable site for pyrheliometer in an urban area.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.