• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2277-2279
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• 2001

This paper describes a vision-based steering control method for AGV which use dual motor drive. We suggest an algorithm which can be detect the guideline quickly and exactly for real time vision processing, and control the steering through an assign the CP (Control - Point) of input image. This method is tested via a IAGV which dual motor drive with a single camera in laboratory environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.38-48
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• 1996

We implemented and evaluated the preformance of a task level pipelined multicomputer "RV860-PIPE(Realtime Vision i860 system using PIPEline)" for computer vision applications. RV860-PIPE is a message-passing MIMD computer having ring interconnection network which is appropriate for vision processing. We designed the node computer of RV860-PIPE using a 64-bit microprocessor to have generality and high processing power for various vision algorithms. Furthermore, to reduce the communication overhead between node computers and between node computer and a frame grabber, we designed dedicated high speed communication channels between them. We showed the practical applicability of the implemented system by evaluting performances of various computer vision applications like edge detection, real-time moving object tracking, and real-time face recognition.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.51-57
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• 2017

Digital signage is becoming part of daily life across a wide range of visual advertisements segments market used in stations, hotels, retail stores, hotels, etc. The current digital signage system used in market is generally works on limited user interactivity with static contents. In this paper, a new approach is proposed using computer vision based dynamic audience adaptive cost-effective digital signage system. The proposed design uses the Camera attached Raspberry Pi Open source platform to employ the real-time audience interaction using computer vision algorithms to extract facial features of the audience. The real-time facial features are extracted using Haar Cascade algorithm which are used for audience gender specific rendering of dynamic digital signage content. The audience facial characterization using Haar Cascade is evaluated on the FERET database with 95% accuracy for gender classification. The proposed system, developed and evaluated with male and female audiences in real-life environments camera embedded raspberry pi with good level of accuracy.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.94-103
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• 2004

The vision system model used for this study involves the six parameters that permits a kind of adaptability in that relationship between the camera space location of manipulable visual cues and the vector of robot joint coordinates is estimated in real time. Also this vision control method requires the number of cameras to transform 2-D camera plane from 3-D physical space, and be used irrespective of location of cameras, if visual cues are displayed in the same camera plane. Thus, this study is to investigate the optimal number of cameras used for the developed vision control system according to the change of the number of cameras. This study is processed in the two ways : a) effectiveness of vision system model b) optimal number of cameras. These results show the evidence of the adaptability of the developed vision control method using the optimal number of cameras.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2531-2533
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• 2005

The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of therm request much memory space and time. Therefore the most reliable neural-network algorithm is drived for real-time matching of obejects, which is composed of a dynamic programming algorithm based on sequence matching techniques in moving objects.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.76-84
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• 1992

The vision system is essential for SMT(Surface Mounting Technology) automation. The system plays the role of matching the positions betweem SMD and PCB, and inspecting SMD in the final stage of mounting. Real-time processing and high-precision are indispensable for practical purpose. In this paper, a new algorithm for position matching and inspection of SMD is proposed, and which is implemented on the DSP board using DSP board using DSP5600. Experimental results show mean matching error within 0.1 mm in the direction of x,y and execution time within 300msec. Therefore, we could attain high-speed and high-precision of the vision system for SMT automation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1637-1645
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• 2004

In remote control of telerobotics equipment, the real-time visual feedback is necessary in order to facilitate real-time control. Because of the network congestion and the associated delays, the real-time image feedback is generally difficult in the public networks like internet. If the remote user is not able to receive the image feedback within a certain time, the work performance may tend to decrease, and it makes difficulties to control of the telerobotics equipment. In this paper, we propose an improved visual feedback scheme over the internet for telerobotics system. The size of a remote site image and its quality are adjusted for efficient transmission. The constructed system has a better real-time update characteristics, and shows a potential for the real-time visual control of the telerobotics system.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.175-181
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• 1998

This paper describes realtime visual tracking system of moving object for three dimensional target using EKF(Extended Kalman Filter). We present a new realtime visual tracking using EKF algorithm and image prediction algorithm. We demonstrate the performance of these tracking algorithm through real experiment. The experimental results show the effectiveness of the EKF algorithm and image prediction algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image.

• International Journal of Korean Welding Society
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• v.4 no.1
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• pp.30-37
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• 2004

There have been continuous efforts on automating welding processes. This automation process could be said to fall into two categories, weld seam tracking and weld quality evaluation. Recently, the attempts to achieve these two functions simultaneously are on the increase. For the study presented in this paper, a vision sensor is made, a vision system is constructed and using this, the 3 dimensional geometry of the bead is measured on-line. For the application as in welding, which is the characteristic of nonlinear process, a fuzzy controller is designed. And with this, an adaptive control system is proposed which acquires the bead height and the coordinates of the point on the bead along the horizontal fillet joint, performs seam tracking with those data, and also at the same time, controls the bead geometry to a uniform shape. A communication system, which enables the communication with the industrial robot, is designed to control the bead geometry and to track the weld seam. Experiments are made with varied offset angles from the pre-taught weld path, and they showed the adaptive system works favorable results.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.2
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• pp.110-116
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• 2005

It is very important to reduce the computational processing time for the application of the vision system in real time such as inspection, the determination of object's dimension and welding etc, because the vision system model involves a lot of measurement data acquired by CCD camera. Also, a lot of computation time is required in estimating the parameters in the vision system model if the iterative batch estimation method such as Newton Raphson is used. Thus, the effective computation method such as the Extended Kalman Filtering(EKF) is required to solve the above problems. The EKF has much advantages in that it takes explicitly into account the measurement uncertainties, and is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm to compute the parameters in the vision system model in real time. This vision system model involves the six parameters to account for the cameras inner and outer parameters. Also the EKF is applied to estimate the object's dimension. Finally, practicality of the estimation scheme of the vision system based on the EKF is verified experimently by performing the estimation of object's dimension.