• 제목/요약/키워드: Computer Vision Technology

검색결과 667건 처리시간 0.027초

슬랜트방식을 이용한 스크류/볼트 선별검사시스템 개발 (Development of the Sorting Inspection System for Screw/Bolt Using a Slant Method)

  • 김용석;양순용
    • 한국생산제조학회지
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    • 제19권5호
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    • pp.698-704
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    • 2010
  • The machine vision system has been widely applied at automatic inspection field of the industries. Especially, the machine vision system shows good performance at difficult inspection field by contact method. In this paper, the automatic system of a slant method to inspect screw/bolt shape using machine vision is developed. The inspection system uses pattern matching method that search similar degree of the lucidity, the average lucidity, length and angle of inspection set up area using a circular scan and a line scan method. Also the feeding method for inspection product is the slant method, and feed rate is controlled by the ramp angle adjustment. This inspection system is composed of a feeding device, a transfer device, vision systems, a lighting device and computer, and is composed the sorting discharge system of the inferior product. The performance test carried out the feeding speed, the shape correct degree and the sorting discharge speed according to the type of screw/bolt. This sorting inspection system showed a satisfied test results in whole inspection items. Presently, this sorting inspection system is being used in the manufacturing process of screw/bolt usefully.

Design of a Low-Cost Micro Robotic System for Developing and Validation Control Algorithms

  • Isarakorn, Don;Suksrimuang, Chatchai;Benjanarasuth, Taworn;Ngamwiwit, Jongkol;Komine, Noriyuki
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1945-1948
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    • 2004
  • This paper describes the design and construction of a micro robotic system addressing such important aspects as versatility and low cost for rapid development and test of new control algorithm. The design and structure of micro robots are presented in detail. The supervision oriented concept is designed for controlling a group of micro robots. In this concept, the vision system recognizes the environment and the host computer decides the micro robot action based on the information from the vision system. In addition, the micro robots can be implemented cheaply and small in size because the structure of supervision oriented system is simplest. The experimental results and the performance of the proposed micro robotic system are discussed.

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저전력 아날로그 CMOS 윤곽검출 시각칩의 설계 (Design of Analog CMOS Vision Chip for Edge Detection with Low Power Consumption)

  • 김정환;박종호;서성호;이민호;신장규;남기홍
    • 센서학회지
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    • 제12권6호
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    • pp.231-240
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    • 2003
  • 고해상도의 윤곽검출 시각칩을 제작하기 위해 윤곽검출 회로의 수를 증가시킬 경우 소비전력 문제 및 회로를 탑재할 칩의 크기를 고려하지 않으면 안된다. 칩을 구성하는 단위회로의 수적 증가는 소비전력의 증가와 더불어 대면적을 요구하게 된다. 소비전력의 증가와 CMOS 생산 회사에서 제공하는 칩의 크기가 수 십 $mm^2$이라는 조건은 결국 단위회로의 수적 증가를 제한하게 된다. 따라서 본 연구에서는, 고해상도의 윤곽검출 시각칩 구현을 위한 윤곽검출 회고의 수적 증가에 따른 전력소비의 최소화 방법으로 전자스위치(electronic switch)가 내장된 윤곽검출 회로를 제안하고, 제한된 칩의 면적에 더 많은 윤곽검출 회로를 넣기 위해 시세포 역할의 광검출 회로와 윤곽검출 회로를 분리하여 구성하는 방법을 적용하였다. $128{\times}128$ 해상도를 갖는 광검출 회고가 $1{\times}128$의 윤곽검출 회고를 공유하여 동일한 칩 면적에 향상된 해상도를 갖는 칩을 설계하였다. 설계된 칩의 크기는 $4mm{\times}4mm$이고, 소비전력은 SPICE 모의실험을 통해 약 20mW가 됨을 확인하였다.

LCD 구동 모듈 PCB의 자동 기능 검사를 위한 Emulated Vision Tester (Emulated Vision Tester for Automatic Functional Inspection of LCD Drive Module PCB)

  • 주영복;한찬호;박길흠;허경무
    • 전자공학회논문지SC
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    • 제46권2호
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    • pp.22-27
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    • 2009
  • 본 논문에서는 LCD 구동 모듈 PCB의 기능 검사를 위한 자동 검사 시스템인 EVT (Emulated Vision Tester)를 제안하고 구현하였다. 기존의 대표적인 자동검사 방법으로는 전기적 검사나 영상기반 검사방식이 있으나 전기적 검사만으로는 Timing이 주요한 변수가 되는 LCD 장비에서는 검출할 수 없는 구동불량이 존재하며 영상기반 검사는 영상획득에 일관성이 결여되거나 Gray Scale의 구분이 불명확하여 검출결과의 재현성이 떨어진다. EVT 시스템은 Pattern Generator에서 인가된 입력 패턴 신호와 구동 모듈을 통한 후 출력되는 디지털 신호를 직접 비교하여 패턴을 검사하고 아날로그 신호 (전압, 저항, 파형)의 이상 여부도 신속 정확하게 검사할 수 있는 하드웨어적인 자동 검사 방법이다. 제안된 EVT 검사기는 높은 검출 신뢰도와 빠른 처리 속도 그리고 간결한 시스템 구성으로 원가 절감 및 전공정 검사 자동화의 실현을 가능케 하는 등 많은 장점을 가진다.

회전 평면경 영상의 단일 카메라 투영에 의한 거리 측정 (Depth Estimation Through the Projection of Rotating Mirror Image unto Mono-camera)

  • 김형석;송재홍;한후석
    • 제어로봇시스템학회논문지
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    • 제7권9호
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    • pp.790-797
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    • 2001
  • A simple computer vision technology to measure the middle-ranged depth with a mono camera and a plain mirror is proposed. The proposed system is structured with the rotating mirror in front of the fixed mono camera. In contrast to the previous stereo vision system in which the disparity of the closer object is larger than that of the distant object, the pixel movement caused by the rotating mirror is bigger for the pixels of the distant object in the proposed system. Being inspired by such distinguished feature in the proposed system, the principle of the depth measurement based on the relation of the pixel movement and the distance of object is investigated. Also, the factors to influence the precision of the measurement are analysed. The benefits of the proposed system are low price and less chance of occlusion. The robustness for practical usage is an additional benefit of the proposed vision system.

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Computer vision monitoring and detection for landslides

  • Chen, Tim;Kuo, C.F.;Chen, J.C.Y.
    • Structural Monitoring and Maintenance
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    • 제6권2호
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    • pp.161-171
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    • 2019
  • There have been a few checking frameworks intended to ensure and improve the nature of their regular habitat. The greater part of these frameworks are constrained in their capacities. In this paper, the insightful checking framework intended for debacle help and administrations has been exhibited. The ideal administrations, necessities and coming about plan proposition have been indicated. This has prompted a framework that depends fundamentally on ecological examination so as to offer consideration and security administrations to give the self-governance of indigenous habitats. In this sense, ecological acknowledgment is considered, where, in light of past work, novel commitments have been made to help include based and PC vision situations. This epic PC vision procedure utilized as notice framework for avalanche identification depends on changes in the normal landscape. The multi-criteria basic leadership strategy is used to incorporate slope data and the level of variety of the highlights. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

A Review of Computer Vision Methods for Purpose on Computer-Aided Diagnosis

  • Song, Hyewon;Nguyen, Anh-Duc;Gong, Myoungsik;Lee, Sanghoon
    • Journal of International Society for Simulation Surgery
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    • 제3권1호
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    • pp.1-8
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    • 2016
  • In the field of Radiology, the Computer Aided Diagnosis is the technology which gives valuable information for surgical purpose. For its importance, several computer vison methods are processed to obtain useful information of images acquired from the imaging devices such as X-ray, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). These methods, called pattern recognition, extract features from images and feed them to some machine learning algorithm to find out meaningful patterns. Then the learned machine is then used for exploring patterns from unseen images. The radiologist can therefore easily find the information used for surgical planning or diagnosis of a patient through the Computer Aided Diagnosis. In this paper, we present a review on three widely-used methods applied to Computer Aided Diagnosis. The first one is the image processing methods which enhance meaningful information such as edge and remove the noise. Based on the improved image quality, we explain the second method called segmentation which separates the image into a set of regions. The separated regions such as bone, tissue, organs are then delivered to machine learning algorithms to extract representative information. We expect that this paper gives readers basic knowledges of the Computer Aided Diagnosis and intuition about computer vision methods applied in this area.

Evaluation of the Damage Mechanism in CFRP Composite Using Computer Vision

  • Kwon, Oh-Heon;Xu, Shaowen;Sutton, Michael
    • Journal of Advanced Marine Engineering and Technology
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    • 제34권5호
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    • pp.686-694
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    • 2010
  • Continuing progress in high technology has created numerous industrial applications for new advanced composite materials. Among these materials, carbon fiber-reinforced plastic (CFRP) laminate composite is typically used for low-weight carrying structures that require high specific strength. In this study, the damage mechanism of a compact tension (CT) specimen of woven CFRP laminates is described in terms of strain and displacement changes and crack growth behavior. The digital image correlation (DIC) method (which is employed here as a computer vision technique) is analyzed. Acoustic emission (AE) characteristics are also acquired during fracture tests. The results demonstrate the usefulness of these methods in evaluating the damage mechanism for woven CFRP laminate composites. From the results, we show these methods are so useful in order to evaluate the damage mechanism for woven CFRP laminate composites.

볼록총채벌레 자동판정을 위한 전처리 (Preprocessing for Automatic Detection of Scirotothrips Dorsalis)

  • 문창배;김병만;이종열;석민웅;현재욱;이평호
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2012년도 춘계학술발표대회논문집
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    • pp.215-218
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    • 2012
  • 농업에 있어 해충 방제는 중요한 일이다. 특히, 볼록총채벌레는 최근 감귤원 해충 피해의 주요 해충으로 인식되어 주기적인 예찰이 이루어지고 있으나 성충의 크기가 0.8mm 정도로 작아 육안 식별에 어려움이 있다. 본 논문에서는 예찰 트랩에 포집된 볼록총채벌레를 자동으로 판별하기 위한 전처리 알고리즘을 제안하였다. 광학 현미경의 배율을 30, 40, 50배로 조정하여 영상을 획득하였고, 제안한 알고리즘을 적용하여 판별 성능을 측정한 결과, 50배율에서 가장 높은 판별율을 보였으나 더 많은 볼록총채벌레 영상을 대상으로 알고리즘을 테스트하고 개선할 필요가 있다.

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객체 검출을 위한 CNN과 YOLO 성능 비교 실험 (Comparison of CNN and YOLO for Object Detection)

  • 이용환;김영섭
    • 반도체디스플레이기술학회지
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    • 제19권1호
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    • pp.85-92
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    • 2020
  • Object detection plays a critical role in the field of computer vision, and various researches have rapidly increased along with applying convolutional neural network and its modified structures since 2012. There are representative object detection algorithms, which are convolutional neural networks and YOLO. This paper presents two representative algorithm series, based on CNN and YOLO which solves the problem of CNN bounding box. We compare the performance of algorithm series in terms of accuracy, speed and cost. Compared with the latest advanced solution, YOLO v3 achieves a good trade-off between speed and accuracy.