• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1316-1319
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• 1996

This paper proposes the algorithm for the correction of a position and orientation of small object such as chip in the precise construction process. In the past, it is general to correct position and orientation of object using human sight and simple vision sensors. But recently, researches using image processing devices have been studied to improve the corrective precision of a position and orientation of object. In this piper, maximum-axis moment and p-theta algorithm are used to correct the position and orientation. Algorithm of maximum-axis moment is widely applied to hetero-object except being applied to a perfect rectangle. This is reason that moments of the X and Y-axis are equal. Therefore, being the shape of a perfect rectangle, the object is applied to other algorithm. In the light of time problem, real-time control is as important as correction of object. To solve it, we use the DSP(Digital Signal Processing) which is far more fast than PC.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.437-441
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• 1997

In the conventional remote monitoring system, a user in front of a computer monitor can acquire only 2 dimensional visual information in a passive way. Thus, even thoght the user finds an interesting object from the video image, helshe can hardly acquire additional information on the object such as name. 311 shape, etc. In this paper, an active monitoring system that shows additional information on the selected object is proposed. The active remote monitoring system can calculate the 3D position of the object that is selected in the video images. Then, using the 3D position of the object, other information on the object can be retrieved from the database and shown on the screen. To calculate the 3D position of the object, 2 CCD cameras that can be tilted and panned using 3 stepping motors are used. The algorithm of 3D position calculation and the result of experiments are explained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.832-834
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• 1999

This paper is a study on the real-position measurements of mobile object using n network. 2-D PSD sensor is used to measure th position of moving object with light source. Position Sensitive Detector(PSD) is an useful which can be used to measure the position o incidence light in accuracy and in real-time. T the position of light source of moving target, neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.68-84
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• 2004

The measured values of a same object should remain constant regardless of the object's position in the image. In other words, its measured values should not vary as its position in the image changes. However, lens' image distortion, heterogeneous light source, varied angle between the measuring apparatus and the object, and different surroundings where the testing is set up will all cause variation in the measurement of the object when the object's position in the image changes. This research attempts to compensate the machine vision image distortion caused by the object's position in the image by developing the compensation table. The compensation is accomplished by facilitating users to obtain the correcting object and serves the objective of improving the precision of measurement.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.555-555
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• 2000

This study is concentrated on the development of hight speed multi-object image processing algorithm, and based on these a1gorithm, vision control scheme is developed for the robot's position control in real time. Recently, the use of vision system is rapidly increasing in robot's position centre. To apply vision system in robot's position control, it is necessary to transform the physical coordinate of object into the image information acquired by CCD camera, which is called image processing. Thus, to control the robot's point position in real time, we have to know the center point of object in image plane. Particularly, in case of rigid body, the center points of multi-object must be calculated in a image plane at the same time. To solve these problems, the algorithm of multi-object for rigid body control is developed.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.104-113
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• 1996

In robot system, the robot manipulation needs the information of task and objects to be handled in possessing a variaty of positions and orientations. In the current industrial robot system, determining position and orientation of objects under industrial environments is one of major problems. In order to pick up an object, the roblt needs the information about the position and orientation of object, and between objects and gripper. When sensing is accomplished by pinhole model camera, the mathematical relationship between object points and their images is expressed in terms of perspective, i.e., central projection. In this paper, a new approach to determine the information of the supporting points related to position and orientation of the object using the robot vision system is developed and testified in experimental setup. The result will be useful for the industrial, agricultural, and autonomous robot.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.129-136
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• 2007

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.

• The Journal of Information Systems
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• v.19 no.1
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• pp.1-17
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• 2010

This paper proposes an updating policy of indoor moving object databases (IMODB) for location-based services. our method applies the Ka1man filter on the recently collected measured positions to estimate the moving object's position and velocity at the moment of the most recent measurement, and extrapolate the current position with the estimated position and velocity. If the distance between the extrapolated current position and the measured current position is within the threshold, in other words if they are close then we skip updating the IMODB. When the IMODB needs to know the moving object's position at a certain moment T, it applies the Kalman filter on the series of the measurements received before T and extrapolates the position at T with the estimations obtained by the Kalman filter. In order to verify the efficiency of our updating method, we performed the experiments of applying our method on the series of measured positions obtained by applying the fingerprinting indoor positioning method while we are actually walking through the test bed. In the analysis of the test results, we estimated the communication saving rate of our method and the error increment rate caused by the communication saving.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1087-1090
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• 2004

stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. In this paper we persent a visual approach to the problem of object grasping. First we propose object recognization method which can find the object position and pose using feature points. A robot recognizes the feature point to Object. So a number of feature point is the more, the better, but if it is overly many, the robot have to process many data, it makes real-time image processing ability weakly. In other to avoid this problem, the robot selects only two point and recognize the object by line made by two points. Second we propose trajectory planing of the robot manipulator. Using grometry of between object and gripper, robot can find a goal point to translate the robot manipulator, and then it can grip the object successfully.