• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.642-646
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• 2008

We have developed a vision based crack detection system and algorithm to inspect base side of bridges. After human operator decides from vision images captured if lines on base side are cracks or dirt, our algorithm finds automatically the length, the width and the shape of cracks. The system has been tested with a robot extender on a truck in real environment and has been proved to be very useful to reduce inspection cost as well as the data management.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.420-425
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• 2003

Generally, reverse engineering means getting CAD data from unidentified shape using vision or 3D laser scanner system. In this paper, we studied unidentified model by machine vision based reverse engineering system to get information about in-processing model. Recently, vision technology is widely used in current factories, because it could inspect the in-process object easily, quickly, accurately. The following tasks were mainly investigated and implemented. We obtained more precise data by corning camera's distortion, compensating slit-beam error and revising acquired image. Much more, we made similar curves or surface with B-spline approximation for precision. Until now, there have been many case study of shape recognition. But it was uncompatible to apply to the field, because it had taken too many processing time and has frequent recognition failure. This paper propose recognition algorithm that prevent such errors and give applications to the field.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.75-80
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• 2008

This paper presents a vision based autonomous inspection system for welding quality control of a RV sinking seat. In order to overcome the precision error that arises from a visible inspection by an operator in the manufacturing process of a RV sinking seat, the machine vision based welding quality control system is proposed. It consists of the CMOS camera and the NI vision system. The geometry of the welding bead, which is the welding quality criteria, is measured by using the captured image with a median filter applied on it. The image processing software for the system was developed using the NI LabVIEW software. The proposed welding quality inspection system for RV sinking seat was verified using experimentation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.479-484
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• 2012

Geometric effect of landmarks to the navigation error is investigated in the two-dimensional line-of-sight measurement based vision navigation system. DOP is derived between line-of-sight measurement error and navigation solution error. For cases of three landmarks in an area, variations of the DOP were observed through computer simulations. Vision navigation system experiments were performed for the cases. Simulation and experimental results show that navigation solution errors have similar trend to DOP values of the simulation.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.96-101
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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 automatic test and assembling in S company.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.71-77
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• 2008

This paper presents a stereo vision based autonomous inspection system for welding quality control of a RV(Recreational Vehicle) sinking seat. The three dimensional geometry of the welding bead, which is the welding quality criteria, is measured by using the captured stereo images with a median filter applied on it. The image processing software for the system was developed using the NI LabVTEW software with NI vision system. In the manufacturing process of a RV sinking seat, the developed system can be used for overcoming the precision error that arises from a visible inspection by an operator. The welding quality inspection system for RV sinking seat was verified using experimentation.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.76-84
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• 2008

This paper is mainly concerned with the vision-based attitude stabilization of a quad-rotor UAV. The methods for attitude control rely on computing the roll and pitch angles of the vehicle from a two-camera vision system. One camera is attached to the body-fixed x-axis and the other to the body-fixed y-axis. The attitude computation for the quad-rotor UAV is performed by image processing consisting of Canny edge and Hough line detection. A proportional and integral controller is employed for the attitude hold autopilot. In this paper, the quad-rotor UAV is modeled by 6-DOF nonlinear equations of motion that includes rotor aerodynamics with blade element theory. The performance of the proposed method is evaluated through 3D environmental numerical simulations.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.553-558
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• 2008

Advancement in information technology have enabled applying vision sensor to railway, such as CCTV. CCTV has been widely used in railway application, however the CCTV is a passive system that provide limited capability to maintain safety from boarding platform. The station employee should monitor continuously CCTV monitors. Therefore immediate recognition and response to the situation is difficultin emergency situation. Recently, urban transit operators are pursuing applying an unattended station operation system for their cost reduction. Therefore, an intelligent monitoring system is need for passenger's safety in railway. The paper proposes a vision based monitoring system and object detection algorithm for passenger's safety in railway platform. The proposed system automatically detects accident in platform and analyzes level of danger using image processing technology. The system uses stereo vision technology with multi-sensors for minimizing detection error in various railway platform conditions.