• Title/Summary/Keyword: Shape Detection

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Active Shape Model with Directional Profile (방향성 프로파일을 적용한 능동형태 모델)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.20 no.11
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    • pp.1720-1728
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    • 2017
  • Active shape model is widely used in the field of image processing especially on arbitrary meaningful shape extraction from single gray level image. Cootes et. al. showed efficient detection of variable shape from image by using covariance and mean shape from learning. There are two stages of learning and testing. Hahn applied enhanced shape alignment method rather than using Cootes's rotation and scale scheme. Hahn did not modified the profile itself. In this paper, the method using directional one dimensional profile is proposed to enhance Cootes's one dimensional profile and the shape alignment algorithm of Hahn is combined. The performance of the proposed method was superior to Cootes's and Hahn's. Average landmark estimation error for each image was 27.72 pixels and 39.46 for Cootes's and 33.73 for Hahn's each.

A Study on Real-Time Defect Detection System Using CNN Algorithm During Scaffold 3D Printing (CNN 알고리즘을 이용한 인공지지체의 3D프린터 출력 시 실시간 출력 불량 탐지 시스템에 관한 연구)

  • Lee, Song Yeon;Huh, Yong Jeong
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.3
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    • pp.125-130
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    • 2021
  • Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.

Development of Crack Examination Algorithm Using the Linearly Integrated Hall Sensor Array (선형 홀 센서 배열을 사용한 결함 검사 알고리즘 개발)

  • Kim, Jae-Jun;Kim, Byoung-Soo;Lee, Jin-Yi;Lee, Soon-Geul
    • Journal of the Korean Society for Precision Engineering
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    • v.27 no.11
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    • pp.30-36
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    • 2010
  • Previous researches show that linearly integrated Hall sensor arrays (LIHaS) can detect cracks in the steel structure fast and effectively This paper proposes an algorithm that estimates the size and shape of cracks for the developed LIHaS. In most nondestructive testing (NDT), just crack existence and location are obtained by processing 1-dimensional data from the sensor that scans the object with relative speed in single direction. The proposed method is composed with two steps. The first step is constructing 2-dimensionally mapped data space by combining the converted position data from the time-based scan data with the position information of sensor arrays those are placed in the vertical direction to the scan direction. The second step is applying designed Laplacian filter and smoothing filter to estimate the size and shape of cracks. The experimental results of express train wheels show that the proposed algorithm is not only more reliable and accurate to detecting cracks but also effective to estimate the size and shape of cracks.

Control of Haptic Hand Controller Using Collision Detection Algorithm (충돌감지 알고리듬을 적용한 햅틱 핸드 컨트롤러의 제어)

  • 손원선;조경래;송재복
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.992-995
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    • 2003
  • A haptic device operated by the user's hand can receive information on position and orientation of the hand and display force and moment generated in the virtual environment to the hand. For realistic haptic display, the detailed information on collision between objects is necessary. In the past, the point-based graphic environment has been used in which the end effector of a haptic device was represented as a point and the interaction of this point with the virtual environment was investigated. In this paper, the shape-based graphic environment is proposed in which the interaction of the shape with the environment is considered to analyze collision or contact more accurately. To this end. the so-called Gilbert-Johnson-Keerthi (GJK) algorithm is adopted to compute collision points and collision instants between two shapes in the 3-D space. The 5- DOF haptic hand controller is used with the GJK algorithm to demonstrate a peg-in-hole operation in the virtual environment in conjunction with a haptic device. It is shown from various experiments that the shape-based representation with the GJK algorithm can provide more realistic haptic display for peg-in-hole operations.

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Multiple damages detection in beam based approximate waveform capacity dimension

  • Yang, Zhibo;Chen, Xuefeng;Tian, Shaohua;He, Zhengjia
    • Structural Engineering and Mechanics
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    • v.41 no.5
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    • pp.663-673
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    • 2012
  • A number of mode shape-based structure damage identification methods have been verified by numerical simulations or experiments for on-line structure health monitoring (SHM). However, many of them need a baseline mode shape generated by the healthy structure serving as a reference to identify damages. Otherwise these methods can hardly perform well when multiple cracks conditions occur. So it is important to solve the problems above. By aid of the fractal dimension method (FD), Qiao and Wang proposed a generalized fractal dimension (GFD) to detect the delamination damage. As a modification of GFD, Qiao and Cao proposed the approximate waveform capacity dimension (AWCD) technique to simplify the calculation of fractal and overcome the false peak appearing in the high mode shapes. Based on their valued work, this paper combined and applied the AWCD method and curvature mode shape data to detect multiple damages in beam. In the end, the identification properties of the AWCD for multiple damages have been verified by groups of Monte Carlo simulations and experiments.

Measure of Effectiveness Analysis of Active SONAR for Detection (능동소나 탐지효과도 분석)

  • Park, Ji-Sung;Kim, Jea-Soo;Cho, Jung-Hong;Kim, Hyoung-Rok;Shin, Kee-Cheol
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.2
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    • pp.118-129
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    • 2013
  • Since the obstacles and mines are of the risk factors for operating ships and submarines, the active sonar system is inevitably used to avoid the hazards in ocean environment. In this paper, modeling and simulation algorithm is used for active sonar systemto quantify the measure of mission achievability, which is known as Measure of Effectiveness(MOE), specifically for detection in this study. MOE for detection is directly formulated as a Cumulative Detection Probability(CDP) calculated from Probability of Detection(PD) in range and azimuth. The detection probability is calculated from Transmission Loss(TL) and the sonar parameters such asDirectivity Index (DI) calculated from the shape of transmitted and received array, steered beam patterns, and Reverberation Level (RL). The developed code is applied to demonstrating its applicability.

Nondestructive Detection of Defect in a Pipe Using Thermography

  • Choi, Hee-Seok;Joung, Ok-Jin;Kim, Young-Han
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1413-1416
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    • 2005
  • An infrared temperature sensor module developed for the detection of defects in a plate was modified to use in a cylinder. A set of optical fiber leads and a mechanism maintaining sensor-object distance constant were utilized for the modification of the IR sensor module. The detection performance was experimentally investigated, and the measured temperature was also compared with computed temperature distribution. The experimental outcome indicates that the detection of a simulated defect is readily available. The temperature distribution is better for defect detection than that with the previous device. In addition, the measured distribution is comparable to the calculated one using a heat conduction equation. The developed device of defect detection is suitable to be utilized in chemical processes where most of vessels and piping systems are in the shape of a cylinder.

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Robust Head Tracking using a Hybrid of Omega Shape Tracker and Face Detector for Robot Photographer (로봇 사진사를 위한 오메가 형상 추적기와 얼굴 검출기 융합을 이용한 강인한 머리 추적)

  • Kim, Ji-Sung;Joung, Ji-Hoon;Ho, An-Kwang;Ryu, Yeon-Geol;Lee, Won-Hyung;Jin, Chung-Myung
    • The Journal of Korea Robotics Society
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    • v.5 no.2
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    • pp.152-159
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    • 2010
  • Finding a head of a person in a scene is very important for taking a well composed picture by a robot photographer because it depends on the position of the head. So in this paper, we propose a robust head tracking algorithm using a hybrid of an omega shape tracker and local binary pattern (LBP) AdaBoost face detector for the robot photographer to take a fine picture automatically. Face detection algorithms have good performance in terms of finding frontal faces, but it is not the same for rotated faces. In addition, when the face is occluded by a hat or hands, it has a hard time finding the face. In order to solve this problem, the omega shape tracker based on active shape model (ASM) is presented. The omega shape tracker is robust to occlusion and illuminationchange. However, whenthe environment is dynamic,such as when people move fast and when there is a complex background, its performance is unsatisfactory. Therefore, a method combining the face detection algorithm and the omega shape tracker by probabilistic method using histograms of oriented gradient (HOG) descriptor is proposed in this paper, in order to robustly find human head. A robot photographer was also implemented to abide by the 'rule of thirds' and to take photos when people smile.

Hierarchical neural network for damage detection using modal parameters

  • Chang, Minwoo;Kim, Jae Kwan;Lee, Joonhyeok
    • Structural Engineering and Mechanics
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    • v.70 no.4
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    • pp.457-466
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    • 2019
  • This study develops a damage detection method based on neural networks. The performance of the method is numerically and experimentally verified using a three-story shear building model. The framework is mainly composed of two hierarchical stages to identify damage location and extent using artificial neural network (ANN). The normalized damage signature index, that is a normalized ratio of the changes in the natural frequency and mode shape caused by the damage, is used to identify the damage location. The modal parameters extracted from the numerically developed structure for multiple damage scenarios are used to train the ANN. The positive alarm from the first stage of damage detection activates the second stage of ANN to assess the damage extent. The difference in mode shape vectors between the intact and damaged structures is used to determine the extent of the related damage. The entire procedure is verified using laboratory experiments. The damage is artificially modeled by replacing the column element with a narrow section, and a stochastic subspace identification method is used to identify the modal parameters. The results verify that the proposed method can accurately detect the damage location and extent.

Feedback scope for fault detection and localization

  • Hunsang Jung;Park, Youngjin
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.32.6-32
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    • 2002
  • The damage localization of the structural system using the natural frequency measurement only is proposed. The existing methods use the changes of mode shape, strain mode shape or curvature mode shape before and after the damage occurrence as these shapes carry the geometric information of the structure. Basically, the change of natural frequencies of the structure can be used as the indicator of the damage occurrence but not as the indicator of the damage location as the natural frequency changes does not carry the geometric information of the structure. In this research, the feedback scope method that measures the natural frequency changes of the structure with and without the feedback Ioo...

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