• Journal of Biosystems Engineering
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• v.32 no.1 s.120
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• pp.44-49
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• 2007

A stereo vision system was developed for robot milking system (RMS) using two monochromatic cameras. An algorithm for inverse perspective transformation was developed for the 3-D information acquisition of all teats. To verify performance of the algorithm in the stereo vision system, indoor tests were carried out using a test-board and model teats. A real cow and a model cow were used to measure distance errors. The maximum distance errors of test-board, model teats and real teats were 0.5 mm, 4.9 mm and 6 mm, respectively. The average distance errors of model teats and real teats were 2.9 mm and 4.43 mm, respectively. Therefore, it was concluded that this algorithm was sufficient for the RMS to be applied.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.161-167
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• 2001

In this study, the control of mounting system for MLGA package was developed using machine vision for the control of rotation position compensation and mounting position of X-Y table. Two types of materials, polymer and alumina, were used for the dielectric insulator of the MLGA. The illumination system and the algorithm of position compensation which is suitable for these materials was developed. We found that the mounting accuracy enough to the degree of${\pm}10{\mu}m$ when MLGA was mounted on the PCB.

• 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.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.265-269
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• 1987

In an industrial vision system, a coding technique for binary image is essential to extract useful informations. To reduce the processing time, a hardware implementation of the chain coding algorithm is attemped. For that purpose, the chain coding algorithm is modified so that it is more suitable for a hardware implementation. A hardwired chain coder is also developed and tested with developed vision system. The result shows that the processing time is greatly reduced and that the developed vision system is maybe feasible for real-time applications.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• Journal of Platform Technology
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• v.10 no.3
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• pp.21-29
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• 2022

Recently, the scope of the smart factory has been expanded, and process research to minimize the part that requires manpower in many processes is increasing. In the case of detecting defects in the appearance of small products, precise verification using a vision system is required. Reliability and speed of inspection are inefficient for human inspection. In this paper, we propose an algorithm for inspecting product appearance defects using a machine vision system. In the case of the remote control targeted in this paper, the appearance is different for each product. Due to the characteristics of the remote control product, the data obtained using two cameras is compared with the master data after denoising and stitching steps are completed. When the algorithm presented in this paper is used, it is possible to detect defects in a shorter time and more accurately compared to the existing human inspection.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.746-751
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• 2006

In this paper, we present tracking algorithm for the indoor moving object. We research passive method using a camera and image processing. It had been researched to use dynamic based estimators, such as Kalman Filter, Extended Kalman Filter and Particle Filter for tracking moving object. These algorithm have a good performance on real-time tracking, but they have a limit. If the shape of object is changed or object is located on complex background, they will fail to track them. This problem will need the complicated image processing algorithm. Finally, a large algorithm is made from integration of dynamic based estimator and image processing algorithm. For eliminating this inefficiency problem, image based estimator, Mean-shift Algorithm is suggested. This algorithm is implemented by color histogram. In other words, it decide coordinate of object's center from using probability density of histogram in image. Although shape is changed, this is not disturbed by complex background and can track object. This paper shows the results in real camera system, and decides 3D coordinate using the data from mean-shift algorithm and relationship of real frame and camera frame.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.649-657
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• 2004

A windshield wiper system plays a key part in assurance of driver's safety at rainfall. However, because quantity of rain and snow vary irregularly according to time and velocity of automotive, a driver changes speed and operation period of a wiper from time to time in order to secure enough visual field in the traditional windshield wiper system. Because a manual operation of wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming direct cause of traffic accident. Therefore, this paper presents the basic architecture of vision-based smart wiper system and the rain sensing algorithm that regulate speed and interval of wiper automatically according to quantity of rain or snow. Also, this paper introduces the fuzzy wiper control algorithm based on human's expertise, and evaluates performance of suggested algorithm in the simulator model. Especially the vision sensor can measure wider area relatively than the optical rain sensor, hence, this grasps rainfall state more exactly in case disturbance occurs.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.119-126
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• 2002

In this paper, we present a new approach based on an elitist genetic algorithm for the task of aligning the position of a robot gripper using CCD cameras. The vision-based control scheme for the task of aligning the gripper with the desired position is implemented by image information. The relationship between the camera space location and the robot joint coordinates is estimated using a camera-space parameter modal that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation. To find the joint angles of a robot manipulator for reaching the target position in the image space, we apply an elitist genetic algorithm instead of a nonlinear least square error method. Since GA employs parallel search, it has good performance in solving optimization problems. In order to improve convergence speed, the real coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using an elitist genetic algorithm with a real coding method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.6
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• pp.486-491
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• 2016

Disturbance/vibration reduction is critical in many applications using machine vision. The off-focusing or blurring error caused by vibration degrades the machine performance. In line with this, real-time disturbance estimation and avoidance are proposed in this study instead of going with a more familiar approach, such as the vibration absorber. The instantaneous motion caused by the disturbance is sensed by an attitude heading reference system module. A periodic vibration modeling is conducted to provide a better performance. The algorithm for vibration avoidance is described according to the vibration modeling. The vibration occurrence function is also proposed, and its parameters are determined using the genetic algorithm. The proposed algorithm is experimentally tested for its effectiveness in the vision inspection system.