• Smart Structures and Systems
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• v.31 no.4
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• pp.393-407
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• 2023

To assess structural condition in a non-destructive manner, computer vision-based structural health monitoring (SHM) has become a focus. Compared to traditional contact-type sensors, the advantages of computer vision-based measurement systems include lower installation costs and broader measurement areas. In this study, we propose a novel computer vision-based vibration measurement and coarse-to-fine damage assessment method for truss bridges. First, a deep learning model FairMOT is introduced to track the regions of interest (ROIs) that include joints to enhance the automation performance compared with traditional target tracking algorithms. To calculate the displacement of the tracked ROIs accurately, a normalized cross-correlation method is adopted to fine-tune the offset, while the Harris corner matching is utilized to correct the vibration displacement errors caused by the non-parallel between the truss plane and the image plane. Then, based on the advantages of the stochastic damage locating vector (SDLV) and Bayesian inference-based stochastic model updating (BI-SMU), they are combined to achieve the coarse-to-fine localization of the truss bridge's damaged elements. Finally, the severity quantification of the damaged components is performed by the BI-SMU. The experiment results show that the proposed method can accurately recognize the vibration displacement and evaluate the structural damage.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.213-213
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• 2000

A sensor system which can measure the transmittance of ITO(Indium Tin Oxide) layed glass is proposed. The sensor system includes a single wavelength laser beam source, photo diodes and electronic circuit processing sensor signal. The wavelength of laser is 543.5 m, this is most sensitive wavelength to photopic and scotopic vision. We applied the sensor to measure transmittance of ITO layer on general manufacturing environment and verified the effectiveness of sensor through experimental measurement.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.155-170
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• 2020

Passive ranging is a critical part of machine vision measurement. Most of passive ranging methods based on machine vision use binocular technology which need strict hardware conditions and lack of universality. To measure the distance of an object placed on horizontal plane, we present a passive ranging method based on monocular vision system by smartphone. Experimental results show that given the same abscissas, the ordinatesis of the image points linearly related to their actual imaging angles. According to this principle, we first establish a depth extraction model by assuming a linear function and substituting the actual imaging angles and ordinates of the special conjugate points into the linear function. The vertical distance of the target object to the optical axis is then calculated according to imaging principle of camera, and the passive ranging can be derived by depth and vertical distance to the optical axis of target object. Experimental results show that ranging by this method has a higher accuracy compare with others based on binocular vision system. The mean relative error of the depth measurement is 0.937% when the distance is within 3 m. When it is 3-10 m, the mean relative error is 1.71%. Compared with other methods based on monocular vision system, the method does not need to calibrate before ranging and avoids the error caused by data fitting.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.34-41
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• 1997

The dimension measurement problem of products has been a major concern in the quality control in the industrial fields. A non-contacting measurement system using the vision sensor is proposed in this paper. The system consists of a CCD camera for the image capture, a frame grabber for the acquired image processing, a laser unit for the illumination, scanning unit for the measurement, and a personal computer for the geometry computation. The slit beam which is generated by passing the laser beam through a cylin- drical lens is fired to the axial-symmetric object on the rotating plate. The image of objects reflected by the laser slit beam, acquired by the CCD camera, becomes much brighter than the other parts of objects. After the histogram of brightness for the captured image is calculated, low intensity pixels are filtered out by threshold method. The performance of proposed measurement system is obtained for several different axial symmetric objects. The proposed system is verified as a good tool for measuring axial-symmetric parts in a limited condition with a minor investment cost.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.06a
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• pp.34-39
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• 2006

An automated surface-strain measurement system, named ASIAS, was developed by using the image processing and stereo vision techniques in the previous studies by the corresponding author and his coworkers. This system has been upgraded mainly to improve the accuracy through image enhancement, sub-pixel measurement, surface smoothing, etc., since the first version was released. The present study has still more improved the convenience of users as well as the accuracy of measurement by processing high resolution images 8 mega pixels or more which can be easily obtained from a portable digital steal camera. It is proved that high resolution image processing greatly decreases the measurement error and gives strain data without considerable deterioration of accuracy even when the deformed grids to be measured and the master grids for camera calibration are captured together in the same image, making the whole process of strain measurement much simpler.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.3
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• pp.61-68
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• 2013

Automatic measurement system is required since cycle time and cost of production are increased by various factors in manual systems. This paper presents a machine vision based prototype measurement system for the automotive axisymmetric shape parts which are generally measured by a manual system that is required the tolerance of the part is very small on each machined surface. This measurement system adopts a method in which optical lens is transferred along the profile of the part to minimize measurement cycle time. The main interest of this paper is a development of an optimum measurement algorithm to the outside diameter of the parts that can be applied to various combinations of hardware. The operating system used to implement the whole system is Window XP and corresponding environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.281-285
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• 1996

In this paper, I made visual inspection system using Vision Board and it is consist of an illuminator (a fluorescent lamp), image input device(CCD(Charge)Coupled Device) camera), image processing system(Vision Board(FARAMVB-02), image output device(videomonitor, printer), a measuring instrument(TELMN1000). Length measurement by visual inspection system is used 100mm gauge block instead of calculating distance between camera and object, it measured horizontal and vertical length factor from 400mm to 650mm by increasing 50mm. In this place, measured horizontal and vertical length factor made use of length measurement of a injection. A measuring instrument used to compare a measured length of a injection visual inspection system with it. In conclusion, length measurement of a injection compared a measuring instrument withvisual inspecion system using length factor of 100mm guage block. Maximum error of length compared two devices a measuring instrument with visual inspection system is 0.55mm. And operation program is made up Borland C++ 3.1. By changing, it is applied to various uses.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.184-191
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• 2007

Autonomous navigation of mobile robot requires a ranging system for measurement of distance to environmental objects. It is obvious that the wider and the faster distance measurement gives a mobile robot more freedom in trajectory planning and control. The active omni-directional ranging system proposed in this paper is capable of obtaining the distance for all 3600 directions in real-time because of the omni-directional mirror and the structured light. Distance computation including the sensitivity analysis and the experiments on the omni-directional ranging are presented to verify the effectiveness of the proposed system.