• Title/Summary/Keyword: Detection Value

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Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection

  • Lee, Jae-Won;Kim, Won-Ki;Oh, Yun-Sik;Seo, Hun-Chul;Jang, Won-Hyeok;Kim, Yoon Sang;Park, Chul-Won;Kim, Chul-Hwan
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.729-739
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    • 2015
  • An algorithm for fault detection and classification method for wide-area protection in Korean transmission systems is proposed. The modeling of 345-kV and 765-kV Korean power system transmission networks using the Electro Magnetic Transient Program - Restructured Version (EMTP-RV) is presented and the algorithm for fault detection and classification in transmission lines is developed. The proposed algorithm uses the Wavelet Transform (WT) and Singular Value Decomposition (SVD). The Singular value of Approximation coefficient (SA) and part Sum of Detail coefficient (SD) are introduced. The characteristics of the SA and SD at the fault conditions are analyzed and used in the algorithm for fault detection and classification. The validation of the proposed algorithm is verified by various simulation results.

Environment Implementation of Real-time Supervisory System Using Motion Detection Method (동작 검출 기법을 이용한 실시간 감시시스템의 구현)

  • 김형균;고석만;오무송
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.999-1002
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    • 2003
  • In this study, embodied supervisory system that apply motion detection technique to small web camera and detects watch picture. Motion detection technique that use pixel value of car image that use in existing need memory to store background image. Also, there is sensitive shortcoming at increase of execution time by data process of pixel unit and noise. Suggested technique that compare extracting motion information by block unit to do to have complexion that solve this shortcoming and is strong at noise. Because motion information by block compares block characteristic value of image without need frame memory, store characteristic cost by block of image. Also, can get effect that reduce influence about noise and is less sensitive to flicker etc.. of camera more than motion detection that use pixel value in process that find characteristic value by block unit.

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Optimal Sensor Placement in Multistatic Sonar (다중 상태 소나의 최적 수신망 배치)

  • Lee, Kwang-Hee;Han, Dong-Seog
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.5
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    • pp.630-634
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    • 2012
  • It is very important to place receiver in multistatic sonar. Inefficient placement of the receiver reduce detection probability and to increase the probability of detection should be used more receivers. Therefore, detection of targets in searching area, detection performance of limited receiver depends on how to place. Through the optimized receiver placement, detection area between each sonar as much as possible avoid duplication, as optimization, the minimum receiver can be maintained detection performance. In this paper we prove mathematical verification of maximum signal excess value based on sonar placement and we calculate a signal excess value by using computer simulations and suggest optimal sonar placement.

Skin Region Detection Using a Mean Shift Algorithm Based on the Histogram Approximation

  • Byun, Ki-Won;Nam, Ki-Gon;Ye, Soo-Young
    • Transactions on Electrical and Electronic Materials
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    • v.13 no.1
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    • pp.10-15
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    • 2012
  • In conventional, skin detection methods using for skin color definitions is based on prior knowledge. By experimentation, the threshold value for dividing the background from the skin region is determined subjectively. A drawback of such techniques is that their performance is dependent on a threshold value which is estimated from repeated experiments. To overcome this, the present paper introduces a skin region detection method. This method uses a histogram approximation based on the mean shift algorithm. This proposed method applies the mean shift procedure to a histogram of a skin map of the input image. It is generated by comparing with the standard skin colors in the $C_bC_r$ color space. It divides the background from the skin region by selecting the maximum value according to the brightness level. As the histogram has the form of a discontinuous function. It is accumulated according to the brightness values of the pixels. It is then, approximated by a Gaussian mixture model (GMM) using the Bezier curve technique. Thus, the proposed method detects the skin region using the mean shift procedure to determine a maximum value. Rather than using a manually selected threshold value, as in existing techniques this becomes the dividing point. Experiments confirm that the new procedure effectively detects the skin region.

Leak Detection Technique of Pressure Vessel Using Acoustic Emission Signal (음향방출 신호를 이용한 압력용기의 누설 검사기법 개발)

  • 이성재;정연식;강명창;김정석
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.4
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    • pp.95-99
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    • 2004
  • In this study, the leak detection technique of pressure vessel by using acoustic emission(AE) signal is suggested experimentally. The leak of pressure vessel is located at the welding line due to welding defects. we measured the AE signal using Rl5I sensor, and examined the AE parameters in leak condition. It is investigated that the mean value of AE signal is dependent on leak source location. So the absolute mean value of AE signal is adopted as dominant AE parameter. We proposed leak detection algorithm using AE signal mean value for monitoring the leak source location.

Scene Change Detection using the Automated Threshold Estimation Algorithm

  • Ko Kyong-Cheol;Rhee Yang-Won
    • The Journal of Information Systems
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    • v.14 no.3
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    • pp.117-122
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    • 2005
  • This paper presents a method for detecting scene changes in video sequences, in which the $chi^{2}$-test is modified by imposing weights according to NTSC standard. To automatically determine threshold values for scene change detection, the proposed method utilizes the frame differences that are obtained by the weighted $chi^{2}$-test. In the first step, the mean and the standard deviation of the difference values are calculated, and then, we subtract the mean difference value from each difference value. In the next step, the same process is performed on the remained difference values, mean-subtracted frame differences, until the stopping criterion is satisfied. Finally, the threshold value for scene change detection is determined by the proposed automatic threshold estimation algorithm. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method is reliably estimates the thresholds and detects scene changes.

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Calculation of the Detection Range for a Given Cumulative Probability in Airborne Surveillance Radars (탐색 레이다에서 누적확률에 기인한 탐지거리 계산에 관한 연구)

  • Kim, Eun Hee;Roh, Ji-Eun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.1
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    • pp.24-27
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    • 2018
  • The performance measure of airborne radars is the range at which the cumulative probability of detection has some specified value, because the per-scan detection probability is an oscillatory function of the target range in airborne radars operating with the dynamic clutter environment. As a result, no one range, at which the per-scan detection probability has a given value, can give a meaningful description of the range performance. In this paper, we provide the equation to calculate the cumulative detection probability and show that the result of Monte Carlo simulation is same as the calculated value in a simple scenario. This verified Monte Carlo model will be used to evaluate the performance of airborne radars in various operating scenarios, at which the numerical calculation is difficult.

Analysis on Optimal Threshold Value for Infrared Video Flame Detection (적외선 영상의 화염 검출을 위한 최적 문턱치 분석)

  • Jeong, Soo-Young;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.8 no.4
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    • pp.100-104
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    • 2013
  • In this paper, we present an optimal threshold setting method for flame detection of infrared thermal image. Conventional infrared flame detection methods used fixed intensity threshold to segment candidate flame regions and further processing is performed to decide correct flame detection. So flame region segmentation step using the threshold is important processing for fire detection algorithm. The threshold should be change in input image depends on camera types and operation conditions. We have analyzed the conventional thresholds composed of fixed-intensity, average, standard deviation, maximum value. Finally, we extracted that the optimal threshold value is more than summation of average and standard deviation, and less than maximum value. it will be enhance flame detection rate than conventional fixed-threshold method.

New Abrupt/Gradual Scene Change Detection (새로운 급진적/점진적 장면 전환 검출)

  • Shin, Seong-Yoon;Rhee, Yang-Wen
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.11
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    • pp.2330-2334
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    • 2009
  • This paper presented a new scene change detection method of compounding color histogram and $x^2$ histogram. This method overcomes the disadvantages of difference value detection methods and will be taking advantage. Also, this method can detect all from the abrupt scene change detection to gradual scene change detection. The proposed method has been compared with previous method, and our experimental results show the better results than the previous method.

A New Efficient Impulse Noise Detection based on Rank Estimation

  • Oh, Jin-Sung;Kim, You-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.3
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    • pp.173-178
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    • 2008
  • In this paper, we present a new impulsive noise detection technique. To remove the impulse noise without detail loss, only corrupted pixels must be filtered. In order to identify the corrupted pixels, a new impulse detector based on rank and value estimations of the current pixel is proposed. Based on the rank and value estimations of the current pixel, the new proposed method provides excellent statistics for detecting an impulse noise while reducing the probability of detecting image details as impulses. The proposed detection is efficient and can be used with any noise removal filter. Simulation results show that the proposed method significantly outperforms many other well-known detection techniques in terms of image restoration and noise detection.

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