• Title/Summary/Keyword: Vision Processing

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A Study on Joint Tracking for Multipass Arc Welding using Vision Sensor (비전 센서를 이용한 다층 아크 용접에서 용접선 추적에 관한 연구)

  • 이정익;장인선;이세현;엄기원
    • Journal of Welding and Joining
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    • v.16 no.3
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    • pp.85-94
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    • 1998
  • Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

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Fundamental research of the target tracking system using a CMOS vision chip for edge detection (윤곽 검출용 CMOS 시각칩을 이용한 물체 추적 시스템 요소 기술 연구)

  • Hyun, Hyo-Young;Kong, Jae-Sung;Shin, Jang-Kyoo
    • Journal of Sensor Science and Technology
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    • v.18 no.3
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    • pp.190-196
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    • 2009
  • In a conventional camera system, a target tracking system consists of a camera part and a image processing part. However, in the field of the real time image processing, the vision chip for edge detection which was made by imitating the algorithm of humanis retina is superior to the conventional digital image processing systems because the human retina uses the parallel information processing method. In this paper, we present a high speed target tracking system using the function of the CMOS vision chip for edge detection.

Design and Implementation of Vision Box Based on Embedded Platform (Embedded Platform 기반 Vision Box 설계 및 구현)

  • Kim, Pan-Kyu;Lee, Jong-Hyeok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.1
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    • pp.191-197
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    • 2007
  • Vision system is an object recognition system analyzing image information captured through camera. Vision system can be applied to various fields, and vehicle recognition is ole of them. There have been many proposals about algorithm of vehicle recognition. But have complex calculation processing. So they need long processing time and sometimes they make problems. In this research we suggested vehicle type recognition system using vision bpx based on embedded platform. As a result of testing this system achieves 100% rate of recognition at the optimal condition. But when condition is changed by lighting, noise and angle, rate of recognition is decreased as pattern score is lowered and recognition speed is slowed.

Detection of Surface Cracks in Eggshell by Machine Vision and Artificial Neural Network (기계 시각과 인공 신경망을 이용한 파란의 판별)

  • 이수환;조한근;최완규
    • Journal of Biosystems Engineering
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    • v.25 no.5
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    • pp.409-414
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    • 2000
  • A machine vision system was built to obtain single stationary image from an egg. This system includes a CCD camera, an image processing board and a lighting system. A computer program was written to acquire, enhance and get histogram from an image. To minimize the evaluation time, the artificial neural network with the histogram of the image was used for eggshell evaluation. Various artificial neural networks with different parameters were trained and tested. The best network(64-50-1 and 128-10-1) showed an accuracy of 87.5% in evaluating eggshell. The comparison test for the elapsed processing time per an egg spent by this method(image processing and artificial neural network) and by the processing time per an egg spent by this method(image processing and artificial neural network) and by the previous method(image processing only) revealed that it was reduced to about a half(5.5s from 10.6s) in case of cracked eggs and was reduced to about one-fifth(5.5s from 21.1s) in case of normal eggs. This indicates that a fast eggshell evaluation system can be developed by using machine vision and artificial neural network.

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A Study on Architecture of Real Time Image Processing System (실시간 영상처리 시스템 구성에 관한 연구)

  • 백남칠;우동민;김영일;최호현
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.4
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    • pp.240-250
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    • 1988
  • This pc-vision system digitizes/displays 512*512*8 bit pixel image in real time and is capable of the various image processing. This system provides a versatile solution to those users pursuing high performance image processing system compatible with the VME bus, and is general purpose imaging system giving the optimal efficiency for machine vision, medical use and various task. In this paper, Image processing technique has classified image enhancement and image analysis in order to design and implement the pc-vision system. In order to improve processing speed, This system unilizing ROI processing performs point operation, local operation and global operation as well as common arithmetic/logic operation in real time.

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Multi-point displacement monitoring of bridges using a vision-based approach

  • Ye, X.W.;Yi, Ting-Hua;Dong, C.Z.;Liu, T.;Bai, H.
    • Wind and Structures
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    • v.20 no.2
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    • pp.315-326
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    • 2015
  • To overcome the drawbacks of the traditional contact-type sensor for structural displacement measurement, the vision-based technology with the aid of the digital image processing algorithm has received increasing concerns from the community of structural health monitoring (SHM). The advanced vision-based system has been widely used to measure the structural displacement of civil engineering structures due to its overwhelming merits of non-contact, long-distance, and high-resolution. However, seldom currently-available vision-based systems are capable of realizing the synchronous structural displacement measurement for multiple points on the investigated structure. In this paper, the method for vision-based multi-point structural displacement measurement is presented. A series of moving loading experiments on a scale arch bridge model are carried out to validate the accuracy and reliability of the vision-based system for multi-point structural displacement measurement. The structural displacements of five points on the bridge deck are measured by the vision-based system and compared with those obtained by the linear variable differential transformer (LVDT). The comparative study demonstrates that the vision-based system is deemed to be an effective and reliable means for multi-point structural displacement measurement.

Built-in CPVS(Concurrent Processing Vision System) of the marking and quality inspection (마킹과 품질검사의 동시 처리 비젼 시스템의 개발)

  • 박화규;채규열;구한서;이윤석;정창성
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.397-399
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    • 2001
  • 레이저를 이용한 마킹(marking) 시스템은 미러(mirror)를 움직이는 XY Scanner안 모터의 Thermal drift로 인한 오차와 laser 오류에 의해 마킹의 불량을 초래하게 된다. 따라서, 이 마킹 불량을 검사하기 위해 마킹 시스템에는 비젼(Vision)을 이용한 검사 장비가 탑재된다. 현재 웨이퍼 마킹기나 다른 마킹기의 비젼시스템은 후검사(post vision) 시스템을 도입하고 있다. 하지만, 후검사 시스템의 경우 마킹이 잘못되었을 때, 바로 마킹을 중지하지 못하고 적어도 한 단위 마킹(tray, 웨이퍼, Strip, PCB 등등)을 망치게 되고, 만일 마킹 대상물이 고가인 경우 상당한 금액의 손실을 가져오는 단점을 가지고 있다. 이러한 단절을 보완하기 위해 본 논문에서는 CPVS(Concurrent Processing Vision System)라는 시스템을 구현하였다. 이 시스템은 마킹과 마킹 품질검사를 동시에 병행함으로써 마킹이 잘못되었을 때 마킹을 중단하게 되어 더 이상의 손실이 나지 않게 하고 후처리 검사 시스템으로의 이송과정을 생략함으로써 processing time을 줄이고, 생산성을 높인다는 장점을 가지게 된다. 이 시스템의 구현은 Visual C++의 MFC 라이브러리를 사용한 MDI구조로 구현하였다.

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Automatic Recognition of In-Process mold Dies Based on Reverse Engineering Technology (형상 역공학을 통한 공정중 금형 가공물의 자동인식)

  • 김정권;윤길상;최진화;김동우;조명우;박균명
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.10a
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    • pp.420-425
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    • 2003
  • Generally, reverse engineering means getting CAD data from unidentified shape using vision or 3D laser scanner system. In this paper, we studied unidentified model by machine vision based reverse engineering system to get information about in-processing model. Recently, vision technology is widely used in current factories, because it could inspect the in-process object easily, quickly, accurately. The following tasks were mainly investigated and implemented. We obtained more precise data by corning camera's distortion, compensating slit-beam error and revising acquired image. Much more, we made similar curves or surface with B-spline approximation for precision. Until now, there have been many case study of shape recognition. But it was uncompatible to apply to the field, because it had taken too many processing time and has frequent recognition failure. This paper propose recognition algorithm that prevent such errors and give applications to the field.

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Further Development of Vision-Based Strain Measurement Methods to Verify Finite Element Analyses

  • Kim, Hyung jong;Lee, Daeyong
    • Transactions of Materials Processing
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    • v.5 no.4
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    • pp.343-352
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    • 1996
  • One of the preferred methods that can be used to verify the results of finite element analysis is to measure surface strains of the deformed part for purpose of direct comparison with simulation results. Instead of using the usual manual method the vision-based measurement method is capable of determining surface geometry and strain from the deformed grid pattern automatically with the help of a computer. To obtain strain distribution over an area, the coordinates of such a surface grid are determined from the multiple video images by applying the photogrammetry principle. Methods to improve the overall accuracy of the vision-based strain measurement system are explored and the possible accuracies that can be attained by such a measurement method are discussed. A major emphasis is placed on the initial grid application method its accuracy and ease of subsequent image processing. Finite element analyses of limiting dome height(LDH) test are carried out and the results of them are compared with exsperimen-tal data.

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The GPU-based Parallel Processing Algorithm for Fast Inspection of Semiconductor Wafers (반도체 웨이퍼 고속 검사를 위한 GPU 기반 병렬처리 알고리즘)

  • Park, Youngdae;Kim, Joon Seek;Joo, Hyonam
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.12
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    • pp.1072-1080
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    • 2013
  • In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.