• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2171-2179
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• 2010

Currently, advanced countries are absorbed in vision research related to 'Technology Convergence', which is a 21 century Megatrend. They establish Technology Convergence strategy based on information and communication technology (ICT), and vision research that utilizes the scenario method is actively progressing. In this paper, scenario-based vision research case study using WWRF (Wireless World Research Forum), AmI (Ambient Intelligence), and mITF (mobile IT Forum) is conducted. The proposed 'engineering scenario method' is based on the case study results. Therefore, a future strategy study using the proposed scenario-based method is analyzed. The 'engineering scenario method' can provide a new direction in vision strategy research.

• Smart Structures and Systems
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• v.20 no.5
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• pp.563-572
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• 2017

The safety of structures is closely associated with the structural out-of-plane behavior. In particular, long and slender beam structures have been increasingly used in the design and construction. Therefore, an evaluation of the lateral and torsional behavior of a structure is important for the safety of the structure during construction as well as under service conditions. The current contact measurement method using displacement meters cannot measure independent movements directly and also requires caution when installing the displacement meters. Therefore, in this study, a vision-based system was used to measure the in-plane and out-of-plane displacements of a structure. The image processing algorithm was based on reference objects, including multiple targets in Lab color space. The captured targets were synchronized using a load indicator connected wirelessly to a data logger system in the server. A laboratory beam test was carried out to compare the displacements and rotation obtained from the proposed vision-based measurement system with those from the current measurement method using string potentiometers. The test results showed that the proposed vision-based measurement system could be applied successfully and easily to evaluating both the in-plane and out-of-plane movements of a beam including twisting rotation.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1041-1051
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• 2014

In this paper, we propose a new image alignment technique based on CUDA SURF in order to solve the initial image alignment problem that frequently occurs in machine vision applications. Machine vision systems using multi-spectral images have recently become more common for solving various decision problems that cannot be performed by the human vision system. These machine vision systems mostly use markers for the initial image alignment. However, there are some applications where the markers cannot be used and the alignment techniques have to be changed whenever their markers are changed. In order to solve these problems, we propose a new image alignment method for multi-spectral machine vision applications based on SURF extracting image features without depending on markers. In this paper, we propose an image alignment method that obtains a sufficient number of feature points from multi-spectral images using SURF and removes outlier iteratively based on a least squares method. We further propose an effective preliminary scheme for removing mismatched feature point pairs that may affect the overall performance of the alignment. In addition, we reduce the execution time by implementing the proposed method using CUDA based on GPGPU in order to guarantee real-time operation. Simulation results show that the proposed method is able to align images effectively in applications where markers cannot be used.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.180.4-180
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• 2001

This paper describes a vision-based line-tracking system for AGV and steering control scheme. For detect the guideline quickly and exactly, We use four line-points which complement and predict each other. This low-cost line-tracking system is efficiently using PC-based real-time vision processing, Steering control is studied through an steering controller with guide-line angle and line-point error. This method is tested via a typical AGV with a single camera in laboratory environment.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.277-280
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• 2004

In recent die industry, web-based production control system is applied widely because of the improvement of IT technology. In result, many researches are published about remote monitoring at a long distance. The target of this study is to develop Die Discrimination System using web-based vision, and CAD API when client discriminates die in process at a long distance. Special feature of this system is to use 2D vision image and to match with DB. We can get discrimination result enough to want with short time and a little low precision in web-monitoring by development of this system.

• Wind and Structures
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• v.21 no.6
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• pp.709-726
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• 2015

In this study, a novel vision-based bolt-loosening monitoring technique is proposed for bolted joints connecting tubular steel segments of the wind turbine tower (WTT) structure. Firstly, a bolt-loosening detection algorithm based on image processing techniques is developed. The algorithm consists of five steps: image acquisition, segmentation of each nut, line detection of each nut, nut angle estimation, and bolt-loosening detection. Secondly, experimental tests are conducted on a lab-scale bolted joint model under various bolt-loosening scenarios. The bolted joint model, which is consisted of a ring flange and 32 sets of bolt and nut, is used for simulating the real bolted joint connecting steel tower segments in the WTT. Finally, the feasibility of the proposed vision-based technique is evaluated by bolt-loosening monitoring in the lab-scale bolted joint model.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.559-563
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• 2000

In this paper we describe a method for aligning a robot gripper using image information. The region of gripper is represented from HSI color model that has major advantage of brightness independence. In order to extract the feature points for vision based position control, we find the corners of gripper shape using polygonal approximation method which determines the segment size and curvature of each points. We apply the vision based scheme to the task of alignment of gripper to reach the desired position by 2 RGB cameras. Experiments are carried out to exhibit the effectiveness of vision based control using feature points from polygonal approximation of gripper.

• Transactions of Materials Processing
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• v.5 no.4
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• pp.343-352
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• 1996

One of the preferred methods that can be used to verify the results of finite element analysis is to measure surface strains of the deformed part for purpose of direct comparison with simulation results. Instead of using the usual manual method the vision-based measurement method is capable of determining surface geometry and strain from the deformed grid pattern automatically with the help of a computer. To obtain strain distribution over an area, the coordinates of such a surface grid are determined from the multiple video images by applying the photogrammetry principle. Methods to improve the overall accuracy of the vision-based strain measurement system are explored and the possible accuracies that can be attained by such a measurement method are discussed. A major emphasis is placed on the initial grid application method its accuracy and ease of subsequent image processing. Finite element analyses of limiting dome height(LDH) test are carried out and the results of them are compared with exsperimen-tal data.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.