• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.471-475
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• 2002

To detect ground subsidence, the permanent scatterer SAR interferometry is applied to the Shinho industrial complex. Eleven JERS-1 images were acquired in the study area between October 1996 and September 1998. All SAR data were co-registered to one master scene (January 8, 1998) and thus 10 interferograms were obtained in a time series. In order to determine permanent scatterers, coherence maps as well as the interferograms were generated and exploited. The coherence at the selected PSs was larger than 0.4 in a 515 sub-window and 0.5 in a 39 sub-window. Twenty-nine PSs within the reclaimed land and 8 PSs (as reference phase) outside the plant were selected for the analysis. The 29 PSs were grouped into 5 sub-groups. We removed the reference phase, which was estimated from 8 outside PSs that were considered as phases free of displacement, from the phases at PSs inside the plant. Residual phases could be interpreted as surface displacement and DEM error. The subsidence of about 40 cm was detected at group 4, while surface displacements were negligible in the rest groups.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.97-100
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• 2013

In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.393-398
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• 2021

Current risk assessment of Spent Nuclear Fuel (SNF) transportation has the problem of the incomplete risk factors consideration and the general particle diffusion model utilization. In this paper, the accident frequency calculation and the detailed simulation of the accident consequences are coupled by the integrated risk assessment method. The "man-machine-environment" three-dimensional comprehensive risk indicator system is established and quantified to characterize the frequency of the transportation accidents. Consideration of vegetation, building and turbulence effect, the standard k-ε model is updated to simulate radioactive consequence of leakage accidents under complex terrain. The developed method is applied to assess the risk of the leakage accident in the scene of the typical domestic SNF Road Transportation (SNFRT). The critical risk factors and their impacts on the dispersion of the radionuclide are obtained.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.544-553
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• 2008

With the development of video editing technology, there are growing uses of overlay text inserted into video contents to provide viewers with better visual understanding. Since the content of the scene or the editor's intention can be well represented by using inserted text, it is useful for video information retrieval and indexing. Most of the previous approaches are based on low-level features, such as edge, color, and texture information. However, existing methods experience difficulties in handling texts with various contrasts or inserted in a complex background. In this paper, we propose a novel framework to localize the overlay text in a video scene. Based on our observation that there exist transient colors between inserted text and its adjacent background a transition map is generated. Then candidate regions are extracted by using the transition map and overlay text is finally determined based on the density of state in each candidate. The proposed method is robust to color, size, position, style, and contrast of overlay text. It is also language free. Text region update between frames is also exploited to reduce the processing time. Experiments are performed on diverse videos to confirm the efficiency of the proposed method.

• Journal of Korea Game Society
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• v.7 no.1
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• pp.43-52
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• 2007

This article describes a new contribution culling method for fast rendering of complex huge urban scenes. A view frustum culling technique is used for fast rendering of complex scenes. To support the levels-of-detail, we subdivide the image regions and construct a weighted quadtree. Only visible objects at the current camera position contributes the current quadtree and the weight is assigned to each object in the quadtree. The weight is proportional to the image area of the projected object, so large buildings in the far distance are less likely to be culled out than small buildings in the near distance. The rendering time is nearly constant not depending on the number of visible objects. The proposed method has applied to a new metropolitan region which is currently under development. Experimental results showed that the rendering quality of the proposed method is barely distinguishable from the rendering quality of the original method, while the proposed method reduces the number of polygons by about 9%. Experimental results showed that the proposed rendering method is appropriate for real-time rendering applications of complex huge scenes.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.321-324
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• 2005

In these days, the management and visualization of 3D geo-spatial information is regarded as one of an important issue in GiS and remote sensing fields. 3D GIS is considered with the database issues such as handling and managing of 3D geometry/topology attributes, whereas 3D visualization is basically concerned with 3D computer graphics. This study focused on the design and implementation for the OpenGL API-based rendering system for the complex types of 3D geo-spatial features. In this approach 3D features can be separately processed with the functions of authoring and manipulation of terrain segments, building segments, road segments, and other geo-based things with texture mapping. Using this implementation, it is possible to the generation of an integrated scene with these complex types of 3D features. This integrated rendering system based on the feature-based 3D-GIS model can be extended and effectively applied to urban environment analysis, 3D virtual simulation and fly-by navigation in urban planning. Furthermore, we expect that 3D-GIS visualization application based on OpenGL API can be easily extended into a real-time mobile 3D-GIS system, soon after the release of OpenGLIES which stands for OpenGL for embedded system, though this topic is beyond the scope of this implementation.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.372-378
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• 2015

Background subtraction is the first processing stage in video surveillance. It is a general term for a process which aims to separate foreground objects from a background. The goal is to construct and maintain a statistical representation of the scene that the camera sees. The output of background subtraction will be an input to a higher-level process. Background subtraction under dynamic environment in the video sequences is one such complex task. It is an important research topic in image analysis and computer vision domains. This work deals background modeling based on modified adaptive Gaussian mixture model (GMM) with three temporal differencing (TTD) method in dynamic environment. The results of background subtraction on several sequences in various testing environments show that the proposed method is efficient and robust for the dynamic environment and achieves good accuracy.

• Smart Media Journal
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• v.2 no.2
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• pp.14-19
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• 2013

Recently, due to the increase of the use of scanned images, the text segmentation techniques, which play critical role to optimize the quality of the scanned images, are required to be updated and advanced. In this study, an algorithm has been developed based on the modification of Gaussian mixture model (GMM) by integrating the calculation of Gaussian detection gradient and the estimation of the number clusters. The experimental results show an efficient method for text segmentation in natural scenes such as storefronts, street signs, scanned journals and newspapers at different size, shape or color of texts in condition of lighting changes and complex background. These indicate that our model algorithm and research approach can address various issues, which are still limitations of other senior algorithms and methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.