• Title/Summary/Keyword: Machine vision algorithm

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Development of an Optimal Trajectory Planning Algorithm for an Automated Pavement Crack Sealer

  • Yoo, Hyun-Seok;Kim, Young-Suk
    • Journal of Construction Engineering and Project Management
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    • v.2 no.1
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    • pp.35-44
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    • 2012
  • In the last two decades, several tele-operated and machine-vision-assisted systems have been developed in the construction and maintenance area, such as pavement crack sealing, sewer pipe rehabilitation, and excavation. In developing such tele-operated and machine-vision-assisted systems, trajectory plans are very important tasks for the optimal motions of robots whether their environments are structured or unstructured. This paper presents an optimal trajectory planning algorithm used for a machine-vision-assisted automatic pavement crack sealing system. In this paper, the performance of the proposed optimal trajectory planning algorithm is compared with the greedy trajectory plans, which are used in the previously developed pavement crack sealing systems. The comparison is based on the computational cost vs. the overall gains in crack sealing efficiency. Finally, it is concluded that the proposed algorithm plays an important role in the productivity improvement of the developed automatic pavement crack sealing system.

An Automated Machine-Vision-based Feeding System for Engine Mount Parts (머신비젼 기반의 엔진마운트 부품 자동공급시스템)

  • Lee, Hyeong-Geun;Lee, Moon-Kyu
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.5
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    • pp.177-185
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    • 2001
  • This paper describes a machine-vision-based prototype system for automatically feeding engine-mount parts to a swaging machine which assembles engine mounts. The system developed consists of a robot, a feeding device with two cylinders and two photo sensors, and a machine vision system. The machine vision system recognizes the type of different parts being fed from the feeding device and estimates the angular difference between the inner-hole center of the part and the point predetermined for assembling. The robot then picks up each part and rotated it through the estimated angle such that the parts are well assembled together as specified. An algorithm has been developed to recognize different part types and estimate the angular difference. The test results obtained for a set of real specimens indicate that the algorithm performs well enough to be applied to prototype system.

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Development of Mounting System for MLAG Chip using Vision (Vision을 이용한 MLGA Chip 장착시스템 개발)

  • 노병옥;강판식
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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    • pp.661-665
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    • 2000
  • In this study, the control of mounting system for MLGA package was developed using machine vision for the control of rotating position compensation and mounting position of X-Y table. Two type of material (polymer, alumina )were used for the dielectric insulator of the MLGA. And the illumination system and the algorithm of position compensation that be suitable for these materials was developed. Also, the position control order that compensated by machine vision actuated to micro stepping motor and X-Y servo motor by controlled PC and mounted the MLGA on PCB in resolution to$\pm10\mum$ .

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A Study on Algorithm for Inspection of Automobile's plastic part locking lever (자동차 플라스틱 부품 락킹레버 검사를 위한 알고리즘 연구)

  • Jang, Bong-Choon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.5
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    • pp.1558-1563
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    • 2010
  • This paper describes a study on algorithm for the development of machine vision system as well as the inspection of automobile's plastic part locking lever to replace a human worker's eye inspection. Before developing the machine vision system based on the PC, the purpose of this research is to develop the algorithm to decide whether a product is a good/bad one in real time inspection. NI-LabVIEW software is used in the inspection method and an inspection program is developed using LabVIEW Vision image functions. The inspection program was built and validated to help the system operator set up the inspection area and change the criteria number in the program.

Development of an Inspection Machine for Automotive Oil-Seals Using Machine Vision (Machine Vision을 이용한 자동차용 Oil-Seal의 불량 검사 기계 개발)

  • 노병국;김도형;박용국
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.3
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    • pp.184-191
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    • 2004
  • In this study, an inspection system for automotive parts using machine vision has been developed and presented. The system is comprised of six analog CCD cameras, frame grabber, and mechanism that loads the automotive parts to the system for the inspection. An Image processing algorithm for detecting eight different types of defects of oil-seals are developed, and the effectiveness of the algorithm is experimentally verified. Inspection process is completed in 1 second with acceptable accuracy. It is envisaged that this inspection system will have a wide application in the automotive part manufacturing industry in the future.

A Machine Vision Algorithm for Measuring the Diameter of Eggcrate Grid (에그크레이트(Eggcrate) 격자(Grid)의 내접원 직경 측정을 위한 머신비편 알고리즘)

  • Kim, Chae-Soo;Park, Kwang-Soo;Kim, Woo-Sung;Hwang, Hark;Lee, Moon-Kyu
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.4
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    • pp.85-96
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    • 2000
  • An Eggcrate assembly is an important part to hold and support 16,000 tubes containing hot and contaminated water in the steam generator of nuclear power plant. As a great number of tubes should be inserted into the eggcrate assembly, the dimensions of each eggcrate grid are one of the critical factors to determine the availability of tube insertion. in this paper. we propose a machine vision algorithm for measuring the inner-circle diameter of each eggcrate grid whose shape is not exact quadrangular. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid height adjustment, and inner-circle diameter estimation. The algorithm is tested on real specimens and the results show that the algorithm works fairly well.

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A Machine Vision Algorithm for the Automatic Inspection of Inserts (인서트 자동검사를 위한 시각인식 알고리즘)

  • 이문규;신승호
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.6
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    • pp.795-801
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    • 1998
  • In this paper, we propose a machine vision algorithm for inspecting inserts which are used for milling and turning operations. Major defects of the inserts are breakage and crack on insert surfaces. Among the defects, breakages on the face of the inserts can be detected through three stages of the algorithm developed in this paper. In the first stage, a multi-layer perceptron is used to recognize the inserts being inspected. Edge detection of the insert image is performed in the second stage. Finally, in the third stage breakages on the insert face are identified using Hough transform. The overall algorithm is tested on real specimens and the results show that the algorithm works fairly well.

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Machine Vision Algorithm Design for Remote Control External Defect Inspection

  • Kang, Jin-Su;Kim, Young-Hyung;Yoon, Sang-Goo;Lee, Yong-Hwan
    • Journal of Platform Technology
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    • v.10 no.3
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    • pp.21-29
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    • 2022
  • Recently, the scope of the smart factory has been expanded, and process research to minimize the part that requires manpower in many processes is increasing. In the case of detecting defects in the appearance of small products, precise verification using a vision system is required. Reliability and speed of inspection are inefficient for human inspection. In this paper, we propose an algorithm for inspecting product appearance defects using a machine vision system. In the case of the remote control targeted in this paper, the appearance is different for each product. Due to the characteristics of the remote control product, the data obtained using two cameras is compared with the master data after denoising and stitching steps are completed. When the algorithm presented in this paper is used, it is possible to detect defects in a shorter time and more accurately compared to the existing human inspection.

A study on the automatic wafer alignment in semiconductor dicing (반도체 절단 공정의 웨이퍼 자동 정렬에 관한 연구)

  • 김형태;송창섭;양해정
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.12
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    • pp.105-114
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    • 2003
  • In this study, a dicing machine with vision system was built and an algorithm for automatic alignment was developed for dual camera system. The system had a macro and a micro inspection tool. The algorithm was formulated from geometric relations. When a wafer was put on the cutting stage within certain range, it was inspected by vision system and compared with a standard pattern. The difference between the patterns was analyzed and evaluated. Then, the stage was moved by x, y, $\theta$ axes to compensate these differences. The amount of compensation was calculated from the result of the vision inspection through the automatic alignment algorithm. The stage was moved to the compensated position and was inspected by vision for checking its result again. Accuracy and validity of the algorithm was discussed from these data.

O-ring Size Measurement Based on a Small Machine Vision Inspection Equipment (소형 머신 비전 검사 장비에 기반한 O링 치수 측정)

  • Jung, YouSoo;Park, Kil-Houm
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.4
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    • pp.41-52
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    • 2014
  • In this paper, O-ring size measurement algorithm based on a small machine vision inspection equipment which can replace a expensive and large machine vision inspection equipment is presented. The small machine vision inspection equipment acquires a image from a CCD camera shooting a measurement plane which located on a back light and the proposed size measurement algorithm is apply to the image. For improvement of size measurement accuracy, camera lens distortion correction and perspective distortion correction are conducted by software technique. Consider O-ring's shape, ellipse fitting model is applied. In order to increase the reliability of ellipse fitting, RANSAC algorithm is applied.