• 제목/요약/키워드: Extraction system

검색결과 3,462건 처리시간 0.028초

A Matlab and Simulink Based Three-Phase Inverter Fault Diagnosis Method Using Three-Dimensional Features

  • Talha, Muhammad;Asghar, Furqan;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권3호
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    • pp.173-180
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    • 2016
  • Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

Content Based Image Retrieval Using Combined Features of Shape, Color and Relevance Feedback

  • Mussarat, Yasmin;Muhammad, Sharif;Sajjad, Mohsin;Isma, Irum
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권12호
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    • pp.3149-3165
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    • 2013
  • Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

Convergence Control of Moving Object using Opto-Digital Algorithm in the 3D Robot Vision System

  • Ko, Jung-Hwan;Kim, Eun-Soo
    • Journal of Information Display
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    • 제3권2호
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    • pp.19-25
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    • 2002
  • In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

영상 검색을 위한 적응적 컴포넌트 분석 시스템 설계 (The Design of Adaptive Component Analysis System for Image Retrieval)

  • 최철;박장춘
    • 한국컴퓨터정보학회지
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    • 제12권1호
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    • pp.9-19
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    • 2004
  • 본 논문에서는 내용 기반 영상 검색 시스템(Content Based Image Retrieval System)의 특징 추출(feature extraction)과 분석(analysis)을 위한 방법으로 적응적 컴포넌트 분석(ACA: Adaptive Component Analysis)을 제안하고 있다. 검색을 위해서 영상에서 추출된 특징들은 영상의 도메인(domain)에 따라 적절하게 적용해야만 좋은 검색 결과를 얻을 수 있다. 이러한 조건을 만족시키기 위한 방법으로 본 논문에서는 검색 측정도(retrieval measurement)를 제안하고 있다. ACA는 알고리즘과 시스템적인 관점에서 볼 때, 기존의 내용 기반 영상 검색을 위한 중간 단계라고 할 수 있으며, 검색 속도 향상 및 성능 개선에 목표를 두고 있다.

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은닉 마르코브 모델을 이용한 비디오 요약 시스템 (Video Summarization Using Hidden Markov Model)

  • 박호식;배철수
    • 한국정보통신학회논문지
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    • 제8권6호
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    • pp.1175-1181
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    • 2004
  • 본 논문에서는 비디오 검색을 위한 비디오 사진 분류 시스템을 제안하였다. 제안된 시스템은 3개의 모듈인 특징 추출, 은닉 마르코브 모델 생성, 그리고 비디오 사진 분류로 구성되어 있다. 같은 등급에 속한 비디오 화면들이 반드시 유사하지 않으므로 견실한 Hidden Markov Model을 구성하기 위해서 는 충분한 학습이 필요하였다. 제안된 시스템은 텔레비전 야구 중계 방송의 비디오 화면을 15가지 등급으로 분류하여 분석 및 하는 실험을 한 결과 평균 84.72%의 인식률을 얻을 수 있었다.

계통연계 풍력발전 시스템의 최대출력 제어를 위한 PI 제어기의 성능 분석 (Performance of PI Controller for Maximum Power Extraction of a Grid-Connected Wind Energy Conversion System)

  • 노경수;류행수
    • 대한전기학회논문지:전력기술부문A
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    • 제51권8호
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    • pp.391-397
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    • 2002
  • This paper presents a modeling and simulation of a PI controller for maximum power extraction of a grid-connected wind energy conversion system with a link of a rectifier and an inverter. It discusses the maximum power control algorithm fnr a wind turbine and proposes, in a graphical form, the relationships of wind turbine output, rotor speed, power coefficient, tip-speed ratio with wind speed when the wind turbine is operated under the maximum power control. The control objective is to always extract maximum power from wind and transfer the power to the utility by controlling both the Pitch angle of the wind turbine blades and the inverter firing angle. Pitch control method is mechanically complicated, but the control performance is better than that of the stall regulation method. The simulation results performed on MATLAB will show the variation of generator's rotor angle and rotor speed, pitch angle, and generator output.

러프 집합 이론을 이용한 3차원 물체 특징 추출 (3D Feature Detection using Rough Set Theory)

  • 정영준;전효병;심귀보
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 G
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    • pp.2222-2224
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    • 1998
  • This paper presents a 3D feature extraction method using rough set theory. Using the stereo cameras, we obtain the raw images and then perform several processes including gradient computation and image matching process. Decision rule constructed via rough set theory determines whether a ceratin point in the image is 3D edge or not. We propose a method finding rules for 3D edge extraction using rough set.

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KNN 분류기에 의한 강판 표면 결함의 분류 (Classification of Surface Defect on Steel Strip by KNN Classifier)

  • 김철호;최세호;김기범;주원종
    • 한국정밀공학회지
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    • 제23권8호
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    • pp.80-88
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    • 2006
  • This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED illuminator and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of hot rolled steel strip are used to develop KNN (k- Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.

표준형상 매개변수 추출을 이용한 자동공정계획 (Automatic Process Planning by Parsing the Parameters of Standard Features)

  • 신동목
    • 한국정밀공학회지
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    • 제20권3호
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    • pp.105-111
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    • 2003
  • This paper presents an approach to automate process planning of press dies for manufacturing of car bodies. Considering that the press-dies used at the same press operations regardless of the panels they produce or the car models of which they produce panels have similar shapes except for the forming part of the dies, general approaches to recognize manufacturing features from CAD models are not necessary. Therefore, a hybrid approach is proposed combining feature-based design and feature-extraction approaches. The proposed method recognizes features by parsing the parameters extracted from CAD models and finds proper operations by querying the database by the recognized features. An internet-based process planning system is developed to demonstrate the proposed approach and to suggest a new paradigm of process planning system that utilizes an internet access to the CAD system.

KNN 분류기에 의한 강판 표면 결함의 분류 (Classification of Surface Defects on Steel Strip by KNN Classifier)

  • 김철호;최세호;주원종;김기범
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 추계학술대회 논문집
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    • pp.379-383
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    • 2005
  • This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED light and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of cold roll steel strips are used to develop KNN (k-Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.

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