• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.91-102
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• 2010

It is very difficult that a previous surveillance system and vehicle detection system find objects on a limited and unstable illumination condition. This paper proposes a robust method of adaptively updating a reference background image for solving problems that are generated by the unstable illumination. The first input image is set up as the reference background image, and is divided into three block categories according to an edge component. Then a block state analysis, which uses a rate of change of the brightness, a stability, a color information, and an edge component on each block, is applied to the input image. On the reference background image, neighbourhood blocks having the same state of a updated block are merged as a block. The proposed method can generate a robust reference background image because it distinguishes a moving object area from an unstable illumination. The proposed method very efficiently updates the reference background image from the point of view of the management and the processing time. In order to demonstrate the superiority of the proposed stable manner in situation that an illumination quickly changes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.5 s.311
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• pp.38-47
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• 2006

Conventional classification method uses a single classifier based on shape or motion feature. However this method exhibits a weakness if naively used since the classification performance is highly sensitive to the accuracy of moving region to be detected. The detection accuracy, in turn, depends on the condition of the image background. In this paper, we propose to resolve the drawback and thus strengthen the classification reliability by employing a Bayesian decision fusion and by optimally combining the decisions of three classifiers. The first classifier is based on shape information obtained from Fourier descriptors while the second is based on the shape information obtained from image gradients. The third classifier uses motion information. Our experimental results on the classification Performance of human and vehicle with a static camera in various directions confirm a significant improvement and indicate the superiority of the proposed decision fusion method compared to the conventional Majority Voting and Weight Average Score approaches.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.32-41
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• 2008

The moving object tracking in vision based observation using video uses difference method between GMM(Gaussian Mixture Model) based background and present image. In the case of racking object using binary image made by threshold, the object is merged not by object information but by Cast-Shadow. This paper proposed the method that eliminates Cast-Shadow using backpropagation Neural Network. The neural network is trained by abstracting feature value form training image of object range in 10-movies and Cast-Shadow range. The method eliminating Cast-Shadow is based on the method distinguishing shadow from binary image, its Performance is better(16.2%, 38.2%, 28.1%, 22.3%, 44.4%) than existing Cast-Shadow elimination algorithm(SNP, SP, DNM1, DNM2, CNCC).

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1187-1200
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• 2002

This paper is concerned with the design or an LMI (Linear Matrix Inequality) -based H$\infty$ controller for a line of sight (LOS) stabilization system and with its robustness performance. The linearization of the system is necessary to analyze various nonlinear characteristics, but the linearization entails modeling uncertainties which reduce its performance. In addition, the stability of the LOS can be adversely affected by angular velocity disturbances while the vehicle is moving. As the vehicle accelerates, all the factors that are Ignored and simplified for the linearization tend to Inhibit the performance of the system. The robustness in the face of these uncertainties needs to be assured. This paper employs H$\infty$ control theory to address these problems and the LMI method to provide a suitable controller with minimal constraints for the system. Even though the system matrix does not have a full rank, the proposed method makes it possible to design a H$\infty$ controller and to deal with R and S matrices for reducing the system order. It can be also shown that the proposed robust controller has a better disturbance attenuation and tracking performance. The LMI method is also used to enhance the applicability of the proposed reduced-order H$\infty$ controller for the system given. The LMI-based H$\infty$ controller has superior disturbance attenuation and reference input tracking performance, compared with that of the conventional controller under real disturbances.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1381-1388
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• 1993

This paper presents a method for the simultaneous optimal design of structural and control systems. Sensitivities of performance index with respect to structural design variables are analyzed. The structural design variables are optimized to minimize the performance index by use of conjugate gradient method. The method is applied to a half model of an active vehicle suspension system with elastic body moving on a randomly profiled road. The suspension control force of an optimally controlled system in the presence of measurement errors are calculated by use of linear quadratic Gaussian control theory and Kalman filter theory. The performance index contains ride comfort, road holding and working space of suspension. The structural design variables taken are stiffness, daming properties and the position of the suspension system. The random road profile considered as colored noise is shaped from white noise by use of shaping filter. The performance of an optimal simultaneous structure/control system is compared with that of an optimal controlled system.

• KIISE Transactions on Computing Practices
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• v.22 no.4
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• pp.189-194
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• 2016

A trajectory is the motion path of a moving object. The advances in IT have made it possible to collect an immeasurable amount of various type of trajectory data from a moving object using location detection devices like GPS. The trajectories of moving objects are widely used in many different fields of research, including the geographic information system (GIS) field. In the GIS field, several attempts have been made to automatically generate digital maps of roads by using the vehicle trajectory data. To achieve this goal, the method to cluster the trajectories on the same road is needed. Usually, the $Fr{\acute{e}}chet$ distance measure is used to calculate the distance between a pair of trajectories. However, the $Fr{\acute{e}}chet$ distance measure requires prolonged calculation time for a large amount of trajectories. In this paper, we presented a fast heuristic algorithm to distinguish whether the trajectories are in close distance or not using the discrete $Fr{\acute{e}}chet$ distance measure. This algorithm trades the accuracy of the resulting distance with decreased calculation time. By experiments, we showed that the algorithm could distinguish between the trajectory within 10 meters and the distant trajectory with 95% accuracy and, at worst, 65% of calculation reduction, as compared with the discrete $Fr{\acute{e}}chet$ distance.

• Journal of Korean Society of Steel Construction
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• v.25 no.4
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• pp.335-346
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• 2013

AASHTO LRFD and Korean Bridge Design Code (Limit State Design) specify to consider Truck and Lane load simultaneously determined from reliability-based live load model, and impact shall be applied to the truck load while it shall not be applied to the lane load. In this paper, vehicle-bridge interaction analysis under moving truck and lane loads were performed to estimate impact factor of the cables and girders for the selected multi-cable-stayed composite bridges with 230m, 400m and 540m main span. A 6-d.o.f. vehicle was used for truck load and a series of single-axle vehicles was applied to simulate equivalent lane load. The effect of damping ratio on the impact factor was estimated and then the essential parameters to impact factor, i.e., road surface roughness and vehicle speed were considered. The road surface roughness was randomly generated based on ISO 8608 and it was applied to the truck load only in the vehicle-bridge interaction analysis. The impact factors evaluated from dynamic interaction analysis were also compared with those by the influence line method that is currently used in design practice to estimate impact factor in cable-stayed bridge.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1155-1161
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• 2001

We propose an adaptive nonlinear control algorithm for high precision tracking and stabilization of LOS(Line-of-Sight). The friction parameters of the LOS gimbal are estimated by off-line evolutionary strategy and the friction is compensated by estimated friction compensator. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Lyapunov stability theory, and its convergence is guaranteed under the limited modeling error or torque disturbance. The performance of the pro-posed algorithm is verified by computer simulation on the LOS gimbal model of a moving vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.140-144
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• 2003

A navigation sensor system for outdoor AGV(Automatic Guided Vehicle) using AMR(Anisotropic Magnetoresitive) sensors is described. We derive a formula of the position of AMR sensor using the measured magnetic field intensity due to permanent magnet with constant distance. The system consists of sensor board. sensor control board and position processing board. The sensor board measures magnetic field intensity, the sensor control board controls the measurement of six sensors sequentially, and the position processing board computes the accurate position of the permanent magnet using Least Square Method. We arranged six sensors at intervals of 30cm and measured the position of the permanent magnet moving at intervals of 30cm. Experimental results showed that we can get standard deviation of 2mm and error of &\pm&4.5mm at a height of 20cm from the permanent magnet.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.125-130
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• 1994

The original concept of GPS is the feature of instantaneous navigation which is the determination of the position of a moving vehicle(ie, a ship, a car, an air craft) by unsmoothed code pseudoranges. The objective of study is compare the efficiency (or time, accuracy) between GPS surveying by using kinematic method and conventional surveying methods in the intersection, and then suggest research materials for actual application.