• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.43-54
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• 2001

In this paper we study the use of polyinstantiation for spatial data, for the purpose of solving cover in topology channel in multilevel secure spatial database systems. Spatial database system with topological structure has a number of spatial analysis function using spatial data and neighbored one\`s each other. But. it has problems that information flow is occurred by topological relationship in spatial database systems. Geographic Information System(CIS) must be needed mandatory access control because there ,are many information flow through positioning information And topological relationship between spatial objects. Moreover, most GIS applications also graphe user interface(GUI). In addressing these problems, we design the MLS/SRDM(Multi Level Security/Spatial Relational Data Model) and propose polyinstantiation for spatial data for solving information flow that occurred by toplogical relationship of spatial data.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.547-553
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• 2021

Dynamic object recognition is an important task for autonomous vehicles. Since dynamic objects exhibit a higher collision risk than static objects, our own trajectories should be planned to match the future state of moving elements in the scene. Time information such as optical flow can be used to recognize movement. Existing optical flow calculations are based only on camera sensors and are prone to misunderstanding in low light conditions. In this regard, to improve recognition performance in low-light environments, we applied a normalization filter and a correction function for Gamma Value to the input images. The low light quality improvement algorithm can be applied to confirm the more accurate detection of Object's Bounding Box for the vehicle. It was confirmed that there is an important in object recognition through image prepocessing and deep learning using YOLO.

• Journal of the Korean Society of Visualization
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• v.3 no.1
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• pp.20-25
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• 2005

An x-ray PIV (Particle Image Velocimetry) technique was developed fur measuring quantitative information on flows inside opaque conduits and/or opaque-fluid flows. To check the performance of the x-ray PIV technique developed, it was applied to a liquid flow in an opaque Teflon tube. To acquire x-ray images suitable for PIV velocity field measurements, the refraction-based edge enhancement mechanism was employed with seeding detectable tracer particles. The amassed velocity field data obtained were in a reasonable agreement with the theoretical prediction. The x-ray PIV technique was also applied to get velocity fields of blood flow and to measure size and velocity of micro-bubbles simultaneously, and to visualize the water refilling process in bamboo leaves. The x-ray PIV was found to be a powerful transmission-type flow imaging technique fur measuring quantitative information of flows inside opaque objects and various opaque-fluid flows.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.240-248
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• 2002

This paper presents a new motion-based segmentation algorithm of moving objects in image sequences. The procedure toward complete segmentation consists of two steps: pixel labeling and motion segmentation. In the first step, we assign a label to each pixel according to magnitude of velocity vector. And velocity vector is generated by optical flow. And, in the second step, we have modeled motion field as a markov random field for noise canceling and make a segmentation of motion through energy minimization. We have demonstrated the efficiency of the presented method through experimental results.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.175-195
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• 1996

In conventional analysis methods, data and process are loosely coupled for building information systems. Several object oriented approaches have been proposed to integrate data and process. However, object oriented analysis requires a radical paradigm and thus system analysts find difficulties in generating object models direcctly from end users. To alleviate these difficulties, this paper proposes a methodology for deriving an object model by using structured analysis results. Objects are obtianed primarily from entities in Entity-Relationship Diagram. Methods are obtained through the analysis of the relationship between processes and data stores in Data Flow Diagram Methods are assigned to the objects by using object/process matrices. A real-life case is illustrated to demonstrate the usefulness of the methodology.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.789-790
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• 2008

In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.546-549
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• 1990

This study introduces the three-dimensional information about moving objects. Relative motion between textured objects and observer generates a time varying optic array at the image, from which image motion of contours can be extracted. Closed-form solutions are proposed for the structure and motion of planar and curved surface patches. The analytic solution for curved surface patches combines the transformation of Longuet-Higgins with the planar surface solution of Subbarao and Waxman. Ovoid patches are shown to construct a unique transform angle. Thus, ovoid patches almost always yield a unique 3D interpretation.

• Journal of the Korea Society for Simulation
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• v.2 no.1
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• pp.1-12
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• 1993

Simulation has been recognized as an invaluable tool in designing and analyzing manufacturing system. In this paper, a Petri net based simulation tool to facilitate the simulation project in manufacturing area is presented . To simulate a manufacturing system, three models are developed ; a Petrinet model, a monitor, and a token control function. While hardware objects in manufacturing systems are modeled by Petri net objects, cell level control functions are separately modeled and integrated with a Petri net model so that they resolve conflicts occuring in Petri net execution. The monitor is a model regarding the information flow between Petri nets and token control functions. The facilities of the developed tool are presented. Also, a modeling procedure with the tool is illustrated via a case study.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.67-72
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• 2015

This paper proposes an object tracking system based on keypoints using homography in mobile environments. The proposed system is based on markerless tracking, and there are four modules which are recognition, tracking, detecting and learning module. Recognition module detects and identifies an object to be matched on current frame correspond to the database using LSH through SURF, and then this module generates a standard object information. Tracking module tracks an object using homography information that generate by being matched on the learned object keypoints to the current object keypoints. Then update the window included the object for defining object's pose. Detecting module finds out the object based on having the best possible knowledge available among the learned objects information, when the system fails to track. The experimental results show that the proposed system is able to recognize and track objects with updating object's pose for the use of mobile platform.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.73-77
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• 2015

This paper proposes an object tracking system according to reliability assessment of learning in mobile environments. The proposed system is based on markerless tracking, and there are four modules which are recognition, tracking, detecting and learning module. Recognition module detects and identifies an object to be matched on current frame correspond to the database using LSH through SURF, and then this module generates a standard object information that has the best reliability of learning. The standard object information is used for evaluating and learning the object that is successful tracking in tracking module. Detecting module finds out the object based on having the best possible knowledge available among the learned objects information, when the system fails to track. The experimental results show that the proposed system is able to recognize and track the reliable objects with reliability assessment of learning for the use of mobile platform.