• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.133-142
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• 1999

We introduce the algorithms of 2-D and 3-D position estimation using 2-D vision sensors. The sensors used in this research issue red laser slit light to the body. So, it is very convenient to obtain the coordinates of corner point or edge in sensor coordinate. Since the measured points are normally not fixed in the body coordinate, the additional conditions, that corner lines or edges are straight and fixed in the body coordinate, are used to find out the position and orientation of the body. In the case of 2-D motional body, we can find the solution analytically. But in the case of 3-D motional body, linearization technique and least mean squares method are used because of hard nonlinearity.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1506-1511
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• 2003

This paper describes an automatic weld seam tracking method of plasma arc welding system designed for the corrugation panel that consists of a linear section and a curved section with various curvatures. Due to the complexity of the panel shape, it is difficult to find a seam and operate a torch manually in the welding process. So, the laser vision sensor for seam tracking is designed for sensing the seam position and controlling a torch automatically. To achieve precise seam tracking, the design of sensor head, image simulation, and calibration are carried out. Through a series of experiment result, compensation algorithm is added and real time error compensation is achieved. The experiment result shows that this vision sensor works effectively. It will provide more precise welding performance and convenience to the operator.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.158-165
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• 2000

Reverse engineering is reproducing products by directly extracting geometric information from physical objects such as clay model wooden mock-up etc. The fundamental work in the reverse engineering is to acquire the geometric data for modeling the objects. This research proposes a novel method for data acquisition aiming at unmanned fast and precise measurement. This is come true by the sensor fusion with CCD camera using structured light beam and touch trigger sensor. The vision system provides global information of the objects data. In this case the number of data and position allocation for touch sensor is critical in terms of the productivity since the number of vision data is very huge. So we applied wavelet transform to reduce the number of data and to allocate the position of the touch probe. The simulated and experimental results show this method is good enough for data reduction.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2444-2446
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• 2003

This paper presents identified locations of obstacles using ultrasonic and vision sensor for mobile robots. An ultrasonic and a vision sensor provide complementary information. To overcome limitations of each sensor, they are combined. To improve effectiveness of detecting of obstacles in image processing, a modified splitting/merging algorithm is proposed. In order to verify effectiveness, proposed algorithm is applied to a mobile robot control system.

• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.96-102
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• 2012

This paper addresses photometric distortion problems of a compact 3D scanning sensor which is composed of a micro-size and inexpensive camera-projector system. Recently, many micro-size cameras and projectors are available. However, erroneous 3D scanning results may arise due to the poor and nonlinear photometric properties of the sensors. This paper solves two inherent photometric distortions of the sensors. First, the response functions of both the camera and projector are derived from the least squares solutions of passive and active calibration, respectively. Second, vignetting correction of the vision camera is done by using a conventional method, however the projector vignetting is corrected by using the planar homography between the image planes of the projector and camera, respectively. Experimental results show that the proposed technique enhances the linear properties of the phase patterns that are generated by the sensor.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.10
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• pp.7-13
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• 2006

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.383-384
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• 2007

• Proceedings of the KWS Conference
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• 2001.05a
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• pp.300-302
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• 2001

This paper describes several advances in vision sensor and process control techniques for applications in Submerged Arc Welding(SAW) which combine to give a fully automatic system capable of controlling and adapting the overall welding process.

• Journal of Biosystems Engineering
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• v.23 no.5
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• pp.481-490
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• 1998

A computer vision system to measure low flow rate of solid particles was developed and tested to examine its performance with various sized 7 kinds of seeds, perilla, mung bean, paddy, small red bean, black soybean, Cuba bean and small potato tuber. The test was performed for two types of particle flow, continuous and discontinuous. For the continuous flow tested with perilla, mung bean and paddy, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method about 0.98. Average errors of the computer vision measurement were in a range of 6∼9%. For the discontinuous flow tested with small red bean, black soybean, Cuba bean and small potato tuber, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method 0.98∼0.99. Average errors of the computer vision measurement were in a range of 5∼10%. Performance of the computer vision system was compared with that of the conventional optical sensor to count particles in discontinuous flow. The comparison was done with black soybean, Cuba bean and small potato tuber, and resulted that the computer vision has much better performance than the optical sensor in a sense of precision of the measurement.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.26-34
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• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.