• Title/Summary/Keyword: vision-based technology

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Development and application of a vision-based displacement measurement system for structural health monitoring of civil structures

  • Lee, Jong Jae;Fukuda, Yoshio;Shinozuka, Masanobu;Cho, Soojin;Yun, Chung-Bang
    • Smart Structures and Systems
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    • v.3 no.3
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    • pp.373-384
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    • 2007
  • For structural health monitoring (SHM) of civil infrastructures, displacement is a good descriptor of the structural behavior under all the potential disturbances. However, it is not easy to measure displacement of civil infrastructures, since the conventional sensors need a reference point, and inaccessibility to the reference point is sometimes caused by the geographic conditions, such as a highway or river under a bridge, which makes installation of measuring devices time-consuming and costly, if not impossible. To resolve this issue, a visionbased real-time displacement measurement system using digital image processing techniques is developed. The effectiveness of the proposed system was verified by comparing the load carrying capacities of a steel-plate girder bridge obtained from the conventional sensor and the present system. Further, to simultaneously measure multiple points, a synchronized vision-based system is developed using master/slave system with wireless data communication. For the purpose of verification, the measured displacement by a synchronized vision-based system was compared with the data measured by conventional contact-type sensors, linear variable differential transformers (LVDT) from a laboratory test.

Vision-Based Eyes-Gaze Detection Using Two-Eyes Displacement

  • Ponglanka, Wirote;Kumhom, Pinit;Chamnongthai, Kosin
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.46-49
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    • 2002
  • One problem of vision-based eye-gazed detection is that it gives low resolution. Base on the displacement of the eyes, we proposed method for vision-based eye-gaze detection. While looking at difference positions on the screen, the distance of the centers of the eyes change accordingly. This relationship is derived and used to map the displacement to the distance in the screen. The experiments are performed to measure the accuracy and resolution to verify the proposed method. The results shown the accuracy of the screen mapping function for the horizontal plane are 76.47% and the error of this function be 23.53%

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Multi-Vision-based Inspection of Mask Ear Loops Attachment in Mask Production Lines (마스크 생산 라인에서 다중 영상 기반 마스크 이어링 검사 방법)

  • JiMyeong, Woo;SangHyeon, Lee;Heoncheol, Lee
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.6
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    • pp.337-346
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    • 2022
  • This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.

Stochastic Model for Unification of Stereo Vision and Image Restoration (스테레오 비젼 및 영상복원 과정의 통합을 위한 확률 모형)

  • Woo, Woon-Tak;Jeong, Hong
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.9
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    • pp.37-49
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    • 1992
  • The standard definition of computational vision is a set of inverse problems of recovering surfaces from images. Thus the common characteristics of the most early vision problems are ill-posed. The main idea for solving ill-posed problems is to restrict the class of admissible solutions by introducing suitable a priori knowledge. Standard regurarization methods lead to satisfactory solutions of early vision problems but cannot deal effectively and directly with a few general problems, such as discontinuity and fusion of information from multiple modules. In this paper, we discuss limitations of standard regularization theory and present new stochastic method. We will outline a rigorous approach to overcome part of ill-posedness of image restoration, edge detection, and stereo vision problems, based on Bayes estimation and MRF(Markov random field) model, that effectively deals with the problems. This result makes one hope that this framework could be useful in the solution of other vision problems.

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Computer Vision-based Structural Health Monitoring: A Review

  • Jun Su Park;Joohyun An;Hyo Seon Park
    • International Journal of High-Rise Buildings
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    • v.12 no.4
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    • pp.321-333
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    • 2023
  • Structural health monitoring is a technology or research field that extends the service life of structures and contributes to the prevention of disaster accidents by continuously evaluating the safety, stability, and serviceability of structures as well as allowing timely and proper maintenance. However, the contact-type sensors used for it require considerable time, cost, and labor for installation and maintenance. As an alternative, computer vision has attracted attention recently. Computer vision has the potential to make quality, deformation, and damage monitoring for structures contactless and automated. In this study, research cases in which computer vision was utilized for structural health monitoring are introduced, and its effects and limitations are summarized. Therefore, the applicability and future research directions of computer vision-based structural health monitoring are discussed.

Calibration for Color Measurement of Lean Tissue and Fat of the Beef

  • Lee, S.H.;Hwang, H.
    • Agricultural and Biosystems Engineering
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    • v.4 no.1
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    • pp.16-21
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    • 2003
  • In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.

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Design of an Intelligent Integrated Control System Using Neural Network (뉴럴 네트워크를 이용한 지능형 통합 제어 시스템 설계)

  • 정동연;김경년;이정호;김원일;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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    • pp.381-386
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    • 2002
  • In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

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A Study on Vision Sensor-based Measurement of Die Location for Its Remodeling (금형 개조 용접시 시각 센서를 이용한 대상물 위치 파악에 관한 연구)

  • Kim, Jitae;Na, Suck-Joo
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.10
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    • pp.141-146
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    • 2000
  • We introduce the algorithms of 3-D position estimation using a laser sensor for automatic die remodeling. First, a vision sensor based on the optical triangulation was used to collect the range data of die surface. Second, line vector equations were constructed by the measured range data, and an analytic algorithm was proposed for recognizing the die location with these vector equations. This algorithm could make the transformation matrix without any specific corresponding points. To ascertain this algorithm, folded SUS plate was measured by the laser vision sensor attached to a 3-axis cartesian manipulator and the transformation matrix was calculated.

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Design of an Intelligent Integrated Control System Using Neural Network (뉴럴 네트워크를 이용한 지능형 통합 제어 시스템 설계)

  • 정동연;이우송;안인모;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2001.04a
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    • pp.217-222
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    • 2001
  • In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

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Design of an Intelligent Robot Control System Using Neural Network (신경회로망을 이용한 지능형 로봇 제어 시스템 설계)

  • 정동연
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2000.04a
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    • pp.182-187
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    • 2000
  • In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for similar model of fifth cell among the twelve cell for automatic test and assemblig in S company.

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