• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.471-478
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• 2011

This UGV (Unmanned Ground Vehicle) is not only widely used in various practical applications but is also currently being researched in many disciplines. In particular, obstacle avoidance is considered one of the most important technologies in the navigation of an unmanned vehicle. In this paper, we introduce a simple algorithm for path planning in order to reach a destination while avoiding a polygonal-shaped static obstacle. To effectively avoid such an obstacle, a path planned near the obstacle is much shorter than a path planned far from the obstacle, on the condition that both paths guarantee that the robot will not collide with the obstacle. So, to generate a path near the obstacle, we have developed an algorithm that combines an edge detection method and a limit-cycle navigation method. The edge detection method, based on Hough Transform and IR sensors, finds an obstacle's edge, and the limit-cycle navigation method generates a path that is smooth enough to reach a detected obstacle's edge. And we proposed novel algorithm to solve local minima using the virtual wall in the local vision. Finally, we verify performances of the proposed algorithm through simulations and experiments.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.164-170
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• 2008

This research was verified detection way of intercept vehicles and performance evaluation after system installation using image detector as detection way of ground installation. By image recognition algorithm was on the trace of moving orbit of violation vehicles for detection way of intercept vehicles. When moving orbit is located special site, utilized geometric image calibration and DC-notch filter. These are cognitive system of license plate by making signal. Then, Bright Evidence Detection and Dark Evidence Detection were applied to after mixing. It is applied to way of Backward tracking for detection way of intercept vehicles. After the field evaluation of developed system, it should be analyzed the more high than recognition rate of minimum standards 80%. It should rise in the estimation of the site applicability is highly from now.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.4
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• pp.80-86
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• 2017

The purpose of this study is to construct a pattern database of pipes and cavities buried in the ground to prevent ground subsidence. To do this, it developed a pattern template algorithm using Open CV and applied it to the results of GPR detection results of tank. As a result, proper pattern database construction was possible. Since the results of this study are based only on limited experimental results, it is expected that more realistic data will be constructed if various field data and detection results of large test beds are supplemented in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.179-186
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• 2015

This paper proposes the target path detection algorithm using statistical characteristics of an activated time lag along a moving path of target from a neighboring sensor in PDR(Pulse Doppler Radar) sensor node environment based on USN(Ubiquitous Sensor Network) with a limitation detecting only an existence of moving target. In the proposed algorithm, detection and non-detection time lag obtained from the experimental data are used. The experimental data are through repetitive action of each 500 times about three path scenarios such as passing in between two sensors, moving parallel to two sensors, and turning through two sensors. From this experiments, error detection percentages of three path scenarios are 5.67%, 5.83%, and 7.17%, respectively. They show that the proposed algorithm can exactly detect a target path using the limited PDR sensor nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5095-5111
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• 2019

A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.95-104
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• 2004

Leaks in underground pipelines can cause social, environmental and economical problems. One of relevant countermeasures against leaks is to find and repair of leak points of the pipes. Leak noise is a good source to identify the location of leak points of the pipelines. Although there have been several methods to detect the leak location with leak noise, such as listening rods, hydrophones or ground microphones, they have not been so efficient tools. In this paper, accelermeters aroused to detect leak locations which could provide an easier and more efficient method. Filtering, signal processing and algorithm of raw input data from sensors for the detection of leak location are described. A 120m-long and a 70m-long experimental pipeline systems are installed and the results with the systems show that the algorithm with the accelerometers offers accurate pinpointing for leaks location detection. Theoretical analysis of sound wave propagation speed of water in underground pipes, which is critically important in leak locating, is also described.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1294-1303
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• 2009

This paper presents a new numerical algorithm for fault discrimination and fault location estimation when occur to arcing ground and arcing line to line on transmission lines. The object of this paper is developed from new numerical algorithm to calculate the fault distance and simultaneously to make a distinction between transient and permanent faults. so the first of object for propose algorithm would be distinguish the permanent from the transient faults. This arcing fault discrimination algorithm is used if calculated value of arc voltage amplitude is greater than product of arc voltage gradient and the length of the arc path, which is equal or greater than the flashover length of a suspension insulator string[1-3]. Also, each algorithm is separated from short distance and long distance. This is difference to with/without capacitance between short to long distance. To test the validity of the proposed algorithms, the results of algorithm testing through various computer simulations are given. The test was simulated in EMTP/ATP simulator under a number of scenarios and calculate of algorithm was used to MATLAB.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.104-115
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• 2005

Median filters in the signal processing have been most widely used and have demonstrated the strongest effects. This paper proposes the adaptive median filters with noise detection. The proposed basic algorithm of the filters is to judge whether or not the noises exist on the ground of The Noise Judgment Standards. Just in case the existence of the noises is verified by the algorithm, it takes the median filter. In order to judge the existence of the noises by the algorithm, this paper introduced the noise detection method by local central variance. As a result of comparing and analyzing the features and performance of the proposed filters and the existing [5]-[10] filters on the same conditions, it was verified that the former proved to be better than the latter, Observed even by naked eyes, it was similar, too. Accordingly, it's proved that the adaptive median filters by local central variance are useful in removing the impulse noise of the median filter and reinforce the edge preservation ability.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.107-112
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• 2018

In this paper, optical flow based keypoint detection and tracking technique is proposed for the collaboration between flying drone with vision system and ground robots. There are many challenging problems in target detection research using moving vision system, so we combined the improved FAST algorithm and Lucas-Kanade method for adopting the better techniques in each feature detection and optical flow motion tracking, which results in 40% higher in processing speed than previous works. Also, proposed image binarization method which is appropriate for the given marker helped to improve the marker detection accuracy. We also studied how to optimize the embedded system which is operating complex computations for intelligent functions in a very limited resources while maintaining the drone's present weight and moving speed. In a future works, we are aiming to develop collaborating smarter robots by using the techniques of learning and recognizing targets even in a complex background.

• Journal of Biomedical Engineering Research
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• v.32 no.1
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• pp.7-14
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• 2011

This study suggested an optimized algorithm for detecting the loss of balance(LOB) in the seated position. And the sensitivity analysis was performed in order to identify the role of each design variable in the algorithm. The LOB algorithm consisted of data processing of measured signals, an internal model of the central nervous system and a control error anomaly(CEA) detector. This study optimized design variables of a CEA detector to obtain improved values of the success rate(SR) of detecting the LOB and the margin time(MT) provided for preventing the falling. Nine healthy adult volunteers were involved in the experiments. All the subjects were asked to balance their body in a predescribed seated posture with the rear legs of a four-legged wooden chair. The ground reaction force from the right leg was measured from the force plate while the accelerations of the chair and the head were measured from a couple of piezoelectric accelerometers. The measured data were processed to predict the LOB using a detection algorithm. Variables S2, h2 and hd are related to the detector: S2 represents a data selecting window, h2 a time shift and hd an operating period of the LOB detection algorithm. S2 was varied from 0.1 to 10 sec with an increment of 0.1 sec, and both h2 and hd were varied from 0.01 to 1.0 sec with an increment of 0.01 sec. It was found that the SR and MT were increased by up to 9.7% and 0.497 sec comparing with the previously published case when the values of S2, h2 and hd were set to 4.5, 0.3 and 0.2 sec, respectively. Also the results of sensitivity analysis showed that S2 and h2 had considerable influence on the SR while these variables were not so sensitive to the MT.