• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.76-84
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• 2012

This paper presents the measurement system of arrow's point of impact using laser scan camera and describes the image calibration method. The calibration process of distorted image is primarily divided into explicit and implicit method. Explicit method focuses on direct optical property using physical camera and its parameter adjustment functionality, while implicit method relies on a calibration plate which assumed relations between image pixels and target positions. To find the relations of image and target position in implicit method, we proposed the performance criteria based polynomial theorem model that overcome some limitations of conventional image calibration model such as over-fitting problem. The proposed method can be verified with 2D position of arrow that were taken by SICK Ranger-D50 laser scan camera.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.41-49
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• 2009

In this paper, the multi-camera calibration algorithm for optical motion capture system is proposed. This algorithm performs 1st camera calibration using DLT(Direct linear transformation} method and 3-axis calibration frame with 7 optical markers. And 2nd calibration is performed by waving with a wand of known length(so called wand dance} throughout desired calibration volume. In the 1st camera calibration, it is obtained not only camera parameter but also radial lens distortion parameters. These parameters are used initial solution for optimization in the 2nd camera calibration. In the 2nd camera calibration, the optimization is performed. The objective function is to minimize the difference of distance between real markers and reconstructed markers. For verification of the proposed algorithm, re-projection errors are calculated and the distance among markers in the 3-axis frame and in the wand calculated. And then it compares the proposed algorithm with commercial motion capture system. In the 3D reconstruction error of 3-axis frame, average error presents 1.7042mm(commercial system) and 0.8765mm(proposed algorithm). Average error reduces to 51.4 percent in commercial system. In the distance between markers in the wand, the average error shows 1.8897mm in the commercial system and 2.0183mm in the proposed algorithm.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.72-77
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• 2023

In many manufacturing settings, including the semiconductor industry, products are completed by producing and assembling various components. Sorting out from randomly mixed parts and classification operations takes a lot of time and labor. Recently, many efforts have been made to select and assemble correct parts from mixed parts using robots. Automating the sorting and classification of randomly mixed components is difficult since various objects and the positions and attitudes of robots and cameras in 3D space need to be known. Previously, only objects in specific positions were grasped by robots or people sorting items directly. To enable robots to pick up random objects in 3D space, bin picking technology is required. To realize bin picking technology, it is essential to understand the coordinate system information between the robot, the grasping target object, and the camera. Calibration work to understand the coordinate system information between them is necessary to grasp the object recognized by the camera. It is difficult to restore the depth value of 2D images when 3D restoration is performed, which is necessary for bin picking technology. In this paper, we propose to use depth information of RGB-D camera for Z value in rotation and movement conversion used in calibration. Proceed with camera calibration for accurate coordinate system conversion of objects in 2D images, and proceed with calibration of robot and camera. We proved the effectiveness of the proposed method through accuracy evaluations for camera calibration and calibration between robots and cameras.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.178-180
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• 2006

In general, camera calibration has to be gone ahead necessarily to estimate a position and an orientation of the object exactly using a camera. Autonomous land system in order to run a vehicle autonomously needs a camera calibration method appling a camera and various road environment. Camera calibration is to prescribe the confrontation relation between third dimension space and the image plane. It means to find camera calibration parameters. Camera calibration parameters using the paved road and the unpaved road are estimated. The proposed algorithm has been detected through the image processing after obtaining the paved road and the unpaved road. There is able to detect easily edges because the road lanes exist in the raved road. Image processing method is two. One is a method on the paved road. Image is segmentalized using open, dilation, and erosion. The other is a method on the unpaved road. Edges are detected using blur and sharpening. So it has been made use of Hough transformation in order to detect the correct straight line because it has less error than least-square method. In addition to, this thesis has been used vanishing point' principle. an algorithm suggests camera calibration method using Hough transformation and vanishing point. When the algorithm was applied, the result of focal length was about 10.7[mm] and RMS errors of rotation were 0.10913 and 0.11476 ranges. these have the stabilized ranges comparatively. This shows that this algorithm can be applied to camera calibration on the raved and unpaved road.

• Journal of the Ergonomics Society of Korea
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• v.19 no.1
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• pp.77-90
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• 2000

The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.596-601
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• 2000

In a robot/vision system, the vision sensor, typically a CCD array sensor, is mounted on the robot hand. The problem of determining the relationship between the camera frame and the robot hand frame is refered to as the hand-eye calibration. In the literature, various methods have been suggested to calibrate camera and for sensor registration. Recently, one-step approach which combines camera calibration and sensor registration is suggested by Horaud & Dornaika. In this approach, camera extrinsic parameters are not need to be determined at all configurations of robot. In this paper, by modifying the camera model and including the lens distortion effect in the perspective transformation matrix, a new one-step approach is proposed in the hand-eye calibration.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.6
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• pp.98-104
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• 2002

In this study, we have developed an algorithm by attaching a camera at the end-effector of industrial six-axis robot in order to determine position and orientation of the camera system from cartesian coordinates. Cartesian coordinate as a starting point to evaluate for suggested algorithm, it was easy to confront increase of orientation vector for a linear line point that connects two points from coordinate space applied by recursive least square method which includes previous data result and new data result according to increase of image point. Therefore, when the camera attached to the end-effector has been applied to production location, with a calibration mask that has more than eight points arranged, this simulation approved that it is possible to determine position and orientation of cartesian coordinates of camera system even without a special measuring equipment.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2333-2335
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• 1998

Recently, the development of computer achieves a system which is similar to the mechanics of human visual system. The 3D measurement using monocular vision system must be achieved a camera calibration. So far, the camera calibration technique required reference target in a scene. But, these methods are inefficient because they have many calculation procedures and difficulties in analysis. Therefore, this paper proposes a native method that without reference target in a scene. We use the grid type frame with different line widths. This method uses vanishing point concept that possess a rotation parameter of the camera and perspective ration that perfect each line widths into a image. We confirmed accuracy of calibration parameter estimation through experiment on the algorithm with a grid paper with different line widths.

• Korean Journal of Computational Design and Engineering
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• v.17 no.1
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• pp.35-44
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• 2012

Many automobile manufacturers are doing experiment on manufacturing environments by using an augmented reality technology. However, system layout and process simulation by using the virtual reality technology have been performed actively more than by using the augmented reality technology in practical use so far. Existing automobile assembly by using the augmented reality requires the precise calibrating work after setting the robot because the existing augmented reality system for the automobile assembly system configuration does not include the end tip deflection and the robot joints deflection due to the heavy weight of product and gripper. Because the robot is used mostly at the automobile assembly, the deflection problem of the robot joint and the product in the existing augmented reality system need to be improved. Moreover camera lens calibration has to be performed precisely to use augmented reality. In order to improve this problem, this paper introduces a method of the software based calibration to apply the augmented reality effectively to the automobile assembly system. On the other hand, the camera lens calibration module and the direct compensation module of the virtual object displacement for the augmented reality were designed and implemented. Furthermore, the developed automobile assembly system oriented AR-system was verified by the practical test.