• 제목/요약/키워드: Machine-vision

검색결과 883건 처리시간 0.032초

TSK 퍼지 시스템을 이용한 카메라 켈리브레이션 (Camera Calibration using the TSK fuzzy system)

  • 이희성;홍성준;오경세;김은태
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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    • pp.56-58
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    • 2006
  • Camera calibration in machine vision is the process of determining the intrinsic cameara parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

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머신비전을 이용한 밸브어셈블리의 3차원 마멸특성 분석 (3D Wear Analysis of Valve Assemblies by Using the Machine Vision)

  • 박창우;정성종
    • 대한기계학회논문집A
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    • 제30권5호
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    • pp.496-504
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    • 2006
  • Wear of engine valves and seat inserts is a major factor affecting engine performance. In order to improve quality and life of valve assemblies, wear mechanism and 3-D surface topography should be analyzed according to operating conditions of the engine. After developing an engine simulator that generates valve speed up to 90Hz and temperature up to $900^{\circ}C$ as well as controls test load, wear experiments have been conducted for two different engine speeds as 10Hz and 25Hz. In order to observe the wear characteristics and monitor surface conditions of the valve assemblies, a cost-effective 3-D wear analysis system based on the shape from focus(SFF) and machine vision has been fabricated in this paper. 3-D surface topography of the valve assemblies has been analyzed to understand the wear behavior according to operating conditions of the engine. Consequently, wear volume of the valve assemblies is quantized by using the developed 3-D wear analysis system.

판타그라프 습판마모의 머신비젼 측정에서 우천시 발생하는 영상의 노이즈 제거방법에 관한 연구 (A Study on an Image Noise Erase Method By to be an Image Noise Frequent Occur for Raining, in Measurement Machine Vision System for using CCD Camera Of Pantograph Sliding Plate Abrasion)

  • 이성권;이대원;김길동;오상윤;김성민
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2007년도 추계학술대회 논문집
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    • pp.872-898
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    • 2007
  • 전동차 자동검사 장치의 하나인 판타그라프 습판마모 자동측정 시스템은 첨단 기술인 머신비젼 기법을 이용하여 습판체의 마모상태를 검수자의 육안검사 없이 마모량과 교체시점 등을 판단하는 시스템이다. 본 논문에서는 우천시 빗물로 인한 노이즈(Noise)가 영상에 입력되어 판타그라프 습판의 에지(Edge)를 검출하는데 영향을 미쳐 신뢰성을 저하시키는 요인이 된다. 이러한 노이즈 제거를 위해 평활화(Smoothing) 처리로서 필터링 기법을 적용한 평균 마스크(Averaging mask), 중간값 필터(Median filter) 기법을 사용하여 문제점 등을 확인하고, 머신비젼 기술에서 사용되는 영상측정에 있어 에지 추출(Edge Detection)이 노이즈의 영향을 받지 않고 안정된 결과를 획득할 수 있도록 유도하고자 한다.

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머신비전을 이용한 PCB 스크린인쇄기의 정렬오차측정 및 위치보정 (1) (Measurement and Correction of PCB Alignment Error for Screen Printer Using Machine Vision (1))

  • 신동원
    • 한국정밀공학회지
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    • 제20권6호
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    • pp.88-95
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    • 2003
  • This paper presents the measurement and correction method of PCB alignment errors for PCB screen printer. Electronic equipment is getting smaller and yet must satisfy high performance standard. Therefore, there is a great demand for PCB with high density. However conventional PCB screen printer doesn't have enough accuracy to accommodate the demand fur high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because the alignment errors of PCB occur when it is loaded to the screen printer. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors with high-accuracy. An automatic optical inspection part measures the PCB alignment errors using machine vision, and the high-accuracy 3-axis stage makes correction for these errors. This system used two CCD cameras to get images of two fiducial marks of PCB. The geometrical relationship between PCB, cameras, and xy$\theta$ stage is derived, and analytical equations for alignment errors are also obtained. The unknown parameters including camera declining angles and etc. can be obtained by initialization process. Finally, the proposed algorithm is verified by experiments by using test bench.

머신비전을 이용한 PCB 스크린인쇄기의 정렬오차측정 및 위치보정 (2) (Measurement and Correction of PCB Alignment Error for Screen Printer Using Machine Vision (2))

  • 신동원
    • 한국정밀공학회지
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    • 제20권6호
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    • pp.96-104
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    • 2003
  • This paper presents the measurement and correction method of PCB alignment errors for PCB screen printer. Electronic equipment is getting smaller and yet must satisfy high performance standard. Therefore, there is a great demand for PCB with high density. However conventional PCB screen printer doesn't have enough accuracy to accommodate the demand for high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because the alignment errors of PCB occur when it is loaded to the screen printer. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors with high-accuracy. An automatic optical inspection part measures the PCB alignment errors using machine vision, and the high-accuracy 3-axis stage makes correction for these errors. This system used two CCD cameras to get images of two fiducial marks of PCB. The centers of fiducial marks are obtained by using moment, gradient method. The first method is calculating the centroid by using first moment of blob, and the latter method is calculating the center of the circle whose equation is obtained by curve-fitting the boundaries of fiducial mark. The operating system used to implement the whole set-up is carried in Window 98 (or NT) environment. Finally we implemented this system to PCB screen printer.

DETECTION AND CLASSIFICATION OF DEFECTS ON APPLE USING MACHINE VISION

  • Suh, Sang-Ryong;Sung, Je-Hoon
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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    • pp.852-862
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    • 1996
  • This study was carried out to develop tools to detect defects of apple using machine vision. For the purpose, 6 kinds of frame for color images, R, G, B, h, S, and I frame, and a frame for near infra-red images (NIR frame) were tested first to select one which is useful to segment defect areas from apple images. After then, several methods to classify kind of defect for the segmented defect areas were developed and tested. Five kinds of apple defect -bruise , decay ,fleck worm hole and scar were investigated . The results are as follows: NIR frame was selected as the best one among the 7 kinds of image frame, and R, G and I frames showed favourable result to segment areas of apple defect. Various features of the segmented defect areas were measured to classify the defect areas. Eight kids of feature of the areas-size, roundness, axes length ratio, mean and variance of pixel values, variance of real part of spectrum, mean and variance of power spectrum resulted from spacial ourier transform were observed for the segmented defect areas in the selected 4 frames. then procedures to classify defects using the features were developed for the 4 frames and tested with 75-113 defects on apples. The test resulted that NIR and I frames showed high accuracies to classify the kind of defect as 77% and 76% , respectively.

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Image Processing Methods for Measurement of Lettuce Fresh Weight

  • Jung, Dae-Hyun;Park, Soo Hyun;Han, Xiong Zhe;Kim, Hak-Jin
    • Journal of Biosystems Engineering
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    • 제40권1호
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    • pp.89-93
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    • 2015
  • Purpose: Machine vision-based image processing methods can be useful for estimating the fresh weight of plants. This study analyzes the ability of two different image processing methods, i.e., morphological and pixel-value analysis methods, to measure the fresh weight of lettuce grown in a closed hydroponic system. Methods: Polynomial calibration models are developed to relate the number of pixels in images of leaf areas determined by the image processing methods to actual fresh weights of lettuce measured with a digital scale. The study analyzes the ability of the machine vision- based calibration models to predict the fresh weights of lettuce. Results: The coefficients of determination (> 0.93) and standard error of prediction (SEP) values (< 5 g) generated by the two developed models imply that the image processing methods could accurately estimate the fresh weight of each lettuce plant during its growing stage. Conclusions: The results demonstrate that the growing status of a lettuce plant can be estimated using leaf images and regression equations. This shows that a machine vision system installed on a plant growing bed can potentially be used to determine optimal harvest timings for efficient plant growth management.

내빙선과 유빙의 충돌을 가정한 예인수조실험 및 머신비전검사를 이용한 유빙의 운동 계측 (Towing Tank Test assuming the Collision between Ice-going Ship and Ice Floe and Measurement of Ice Floe's Motion using Machine Vision Inspection)

  • 김효일;전승환
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2015년도 추계학술대회
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    • pp.33-34
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    • 2015
  • 북극항로(NSR)를 통항하는 상선과 화물량이 매년 중가추세에 있다. 쇄빙선의 도움을 받아 북극항로를 통항하는 상선의 안전한 항해를 위협하는 가장 큰 요인은 얼음과의 충돌이다. 따라서 선박과 얼음의 충돌 메커니즘을 규명하기 위한 노력이 관련 연구자들에 의해서 활발히 이루어지고 있다. 본 연구에서는 북극항로를 운항하는 내빙선과 유빙의 충돌을 가정한 예인수조실험을 실시하며, 충돌 후 얼음의 운동(속력, 궤적)을 머신비전검사를 통해서 계측한다. 아울러 오차계산을 통해서 머신비전검사 기법의 정밀도를 검증한다.

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멀티센서 시스템을 이용한 3차원 형상의 기상측정에 관한 연구 (A Study on the 3-dimensional feature measurement system for OMM using multiple-sensors)

  • 권양훈;윤길상;조명우
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 추계학술대회 논문집
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    • pp.158-163
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    • 2002
  • This paper presents a multiple sensor system for rapid and high-precision coordinate data acquisition in the OMM (On-machine measurement) process. In this research, three sensors (touch probe, laser, and vision sensor) are integrated to obtain more accurate measuring results. The touch-type probe has high accuracy, but is time-consuming. Vision sensor can acquire many point data rapidly over a spatial range but its accuracy is less than other sensors. Also, it is not possible to acquire data for invisible areas. Laser sensor has medium accuracy and measuring speed among the sensors, and can acquire data for sharp or rounded edge and the features with very small holes and/or grooves. However, it has range- constraints to use because of its system structure. In this research, a new optimum sensor integration method for OMM is proposed by integrating the multiple-sensor to accomplish mote effective inspection planning. To verify the effectiveness of the proposed method, simulation and experimental works are performed, and the results are analyzed.

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머신비전을 이용한 도로상의 보행자 검출에 관한 연구 (A Study on the Pedestrian Detection on the Road Using Machine Vision)

  • 이병룡;;김형석;배용환
    • 제어로봇시스템학회논문지
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    • 제17권5호
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    • pp.490-498
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    • 2011
  • In this paper, we present a two-stage vision-based approach to detect multi views of pedestrian in road scene images. The first stage is HG (Hypothesis Generation), in which potential pedestrian are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map, and different colors between road background and pedestrian's clothes to determine the leg position of pedestrian, then a novel symmetry peaks processing is performed to define how many pedestrians is covered in one potential candidate region. Finally, the real candidate region where pedestrian exists will be constructed. The second stage is HV (Hypothesis Verification). In this stage, all hypotheses are verified by Support Vector Machine for classification, which is robust for multi views of pedestrian detection and recognition problems.