• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.10
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• pp.620-629
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• 2005

In this paper, a new protocol-based approach was proposed for development of a ubiquitous vision system. It is possible to apply the approach by regarding the ubiquitous vision system as a multiagent system. Thus, each vision sensor can be regarded as an agent (vision agent). Each vision agent independently performs exact segmentation for a target by color and motion information, visual tracking for multiple targets in real-time, and location estimation by a simple perspective transform. Matching problem for the identity of a target during handover between vision agents is solved by the Identified Contract Net (ICN) protocol implemented for the protocol-based approach. The protocol-based approach by the ICN protocol is independent of the number of vision agents and moreover the approach doesn't need calibration and overlapped region between vision agents. Therefore, the ICN protocol raises speed, scalability, and modularity of the system. The protocol-based approach was successfully applied for our ubiquitous vision system and operated well through several experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.496-504
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• 2009

This paper presents a recognition performance of VOR (Vestibular-Ocular Reflex) based vision tracking system for mobile robot. The VOR is a reflex eye movement which, during head movements, produces an eye movement in the direction opposite to the head movement, thus maintaining the image of interested objects placed on the center of retina. We applied this physiological concept to the vision tracking system for high recognition performance in mobile environments. The proposed method was implemented in a vision tracking system consisting of a motion sensor module and an actuation module with vision sensor. We tested the developed system on an x/y stage and a rate table for linear motion and angular motion, respectively. The experimental results show that the recognition rates of the VOR-based method are three times more than non-VOR conventional vision system, which is mainly due to the fact that VOR-based vision tracking system has the line of sight of vision system to be fixed to the object, eventually reducing the blurring effect of images under the dynamic environment. It suggests that the VOR concept proposed in this paper can be applied efficiently to the vision tracking system for mobile robot.

• Wind and Structures
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• v.20 no.2
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• pp.315-326
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• 2015

To overcome the drawbacks of the traditional contact-type sensor for structural displacement measurement, the vision-based technology with the aid of the digital image processing algorithm has received increasing concerns from the community of structural health monitoring (SHM). The advanced vision-based system has been widely used to measure the structural displacement of civil engineering structures due to its overwhelming merits of non-contact, long-distance, and high-resolution. However, seldom currently-available vision-based systems are capable of realizing the synchronous structural displacement measurement for multiple points on the investigated structure. In this paper, the method for vision-based multi-point structural displacement measurement is presented. A series of moving loading experiments on a scale arch bridge model are carried out to validate the accuracy and reliability of the vision-based system for multi-point structural displacement measurement. The structural displacements of five points on the bridge deck are measured by the vision-based system and compared with those obtained by the linear variable differential transformer (LVDT). The comparative study demonstrates that the vision-based system is deemed to be an effective and reliable means for multi-point structural displacement measurement.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.923-928
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• 1990

This paper describes the design and implementation of a real-time, high-precision vision system and its application to SMT(surface mounting technology) automation. The vision system employs a 32 bit MC68030 as a main processor, and consists of image acquisition unit. DSP56001 DSP based vision processor, and several algorithmically dedicated hardware modules. The image acquisition unit provides 512*480*8 bit image for high-precision vision tasks. The DSP vision processor and hardware modules, such as histogram extractor and feature extractor, are designed for a real-time excution of vision algorithms. Especially, the implementation of multi-processing architecture based on DSP vision processors allows us to employ more sophisticated and flexible vision algorithms for real-time operation. The developed vision system is combined with an Adept Robot system to form a complete SMD system. It has been found that the vision guided SMD assembly system is able to provide a satisfactory performance for SND automation.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.95-101
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• 2013

The paper investigates the geometric effect of landmarks to the navigation error in the landmark based 3D vision navigation and introduces the INS/Vision integrated navigation system considering its effect. The integrated system uses the vision navigation results taking into account the dilution of precision for landmark geometry. Also, the integrated system helps the vision navigation to consider it. An indirect filter with feedback structure is designed, in which the position and the attitude errors are measurements of the filter. Performance of the integrated system is evaluated through the computer simulations. Simulation results show that the proposed algorithm works well and that better performance can be expected when the error characteristics of vision navigation are considered.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2379-2384
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• 2005

We propose a novel method for object recognition using the smart tag system with a stereo vision on a pan-tilt mechanism. We developed a smart tag which included IRED device. The smart tag is attached onto the object. We also developed a stereo vision system which pans and tilts for the object image to be the centered on each whole image view. A Stereo vision system on the pan-tilt mechanism can map the position of IRED to the robot coordinate system by using pan-tilt angles. And then, to map the size and pose of the object for the robot to coordinate the system, we used a simple model-based vision algorithm. To increase the possibility of tag-based object recognition, we implemented our approach by using as easy and simple techniques as possible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1601-1607
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• 2009

Vision system is an object recognition system analyzing image information captured through camera. Vision system can be applied to various fields, and automobile types recognition is one of them. There have been many research about algorithm of automobile types recognition. But have complex calculation processing. so they need long processing time. In this paper, we designed vision box based on embedded system. and suggested automobile types recognition system using the vision box. As a result of pretesting, this system achieves 100% rate of recognition at the optimal condition. But when condition is changed by lighting and angle, recognition is available but pattern score is lowered. Also, it is observed that the proposed system satisfy the criteria of processing time and recognition rate in industrial field.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.605-607
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• 1997

According to the way of the robot control, the robot systems of all the teams which participate in the MIROSOT can be divided into three categories : the remote brainless system, the vision-based system and the robot-based system. The MIRAGE I robot control system uses the last one, the robot-based system. In the robot-based system the host computer with the vision system transmits the data on only the location of the ball and the robots. Based on this robot control method, we took part in the MIROSOT '96 and the MIROSOT '97.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.101-104
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• 1987

This paper shows the robot-vision system which consists of robot, vision system, single board computer and IBM-PC. IBM-PC based system has a great flexibility in expansion for a vision system interfacing. Easy human interfacing and great calculation ability are the benefits of this system. It was carried to interface between each component. The calibration between two coordinate systems is studied. The robot language for robot-vision system was written in "C" language. User also can write job program in "C" language in which the robot and vision related functions reside in the library.side in the library.