• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.14-21
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• 2003

With the increased use of lasers in industrial welding applications, techniques for monitoring and controlling these processes become increasingly important. It is very important that we understand the dynamic behaviors of the laser induced Plume in welding, because the laser induced plume has considerable effects on welding efficiency and the quality of materials. As the plume fluctuation was associated with keyhole instability, unstable vapor plume indicated the process was unstable and would result in poor welds. An Infrared Thermal-vision Camera can be utilized compensate for incurracies encountered in real-time monitoring during laser welding. We have results that instabilities of plume are closely related with hot cracking and defect of laser welding.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.4
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• pp.268-273
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• 2003

In the present study, the characteristics of upward bubble flow were experimentally investigated in a liquid bath. An electro-conductivity probe was used to measure local volume fraction and bubble frequency. Since the gas is concentrated at the near nozzle, the flow parameters are high near the nozzle. In general their axial and radial values tended to decrease with increasing distance. For visualization of flow characteristics, a Particle Image Velocimetry (P.I..V) and a thermo-vision camera were used in the present study. The experimental results show that heat transfer from bubble surface to water is largely completed within z=10mm from the nozzle, and then the temperature of bubble surface reaches that of water rapidly. Due to the centrifugal force, the flow was more developed near the wall than at bubble-water plume. Vortex flow in the bottom region was relatively weaker than that in the upper region.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.144-151
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• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.82-87
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• 1998

In this study, the theoretical resolution analysis of an active vision system using laser range finder is performed for surrounding recognition and 3D data acquisition in unknown environment. In the result, the resolution of range data in laser range finder is depend on the distance between lens center of CCD camera and light emitter, view angle, beam angle, and parameters of CCD camera. The theoretical resolutions of the laser range finders of various types which are based on parameters effected resolution are calculated and experimental results are obtained in real system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.115-120
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• 2000

This study is on the application the image processing algorithm for inspection of the aluminium mill strip surface defect. The image of surface defect data was obtained using the CCD camera with the digital signal board. The edge was found from the difference of pixel intensity between the normal image and defect image. Two step were taken to find the edge in the image processing algorithm. First, noise was removed by using the median filter in the image. Second, the edge was sharpened in detail by using the sharpening convolution filter in the image. Canny algorithm was used to defect the exact edge. The defect section was separated from the original image is to find the coordination point p1 and p2 which include the defect image

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.135-140
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• 2017

SMT is an equipment that picks up electronic components and does precise placing onto PCBs. In order to do this, it stops in front of a camera installed in the middle to go over vision inspection. And after that it is move for placing. In this paper, We compared to the method of the placing after inspect to the stoped component and the moving component in front of the camera. As a result, This paper shows that the time efficiency of the fly-motion was increased by 9 percent than the stop-motion.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.159-165
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• 2012

The accurate focusing position should be determined for accurate measurements In VMS. Camera lens focusing is an important problem in computer vision and video measuring systems (VMS) that use CCD cameras and high precision XYZ stages. Camera focusing is a very important step in high precision measurement systems that use computer vision technique. The auto focusing process consists of two steps, the focus value measurement step and the exact focusing position determination step. It is suitable for eliminating high frequency noises with lower processing time and without blurring. An automatic focusing technique is applied to measure a crater with a one-dimensional search algorithm for finding the best focus. Throughout this paper, the suggested algorithm for the Auto focusing was combined with the learning. As a result, it is expected that such a combination would be expanded into the system of recognizing voices in a noisy environment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.149-149
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• 2000

We experimented on AGV driving test with color CCD camera which is setup on it. This paper can be divided into two parts. One is image processing part to measure the condition of the guideline and AGV. The other is part that obtains the reference steering angle through using the image processing parts. First, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, AGV knows the driving conditions of AGV. After then using of those information, AGV calculates the reference steering angle changed by the speed of AGV. In the case of low speed, it focuses on the left/right error values of the guide line. As increasing of the speed of AGV, it focuses on the slop of guide line. Lastly, we are to model the above descriptions as the type of PID controller and regulate the coefficient value of it the speed of AGV.