• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.297-304
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• 1997

In stereo vision, camera modeling is very important because the accuracy of the three dimensional locations depends considerably on it. In the existing stereo camera models, two camera planes are located in the same plane or on the optical axis. These camera models cannot be used in the active vision system where it is necessary to obtain two stereo images simultaneously. In this paper, we propose four kinds of stereo camera models for active stereo vision system where focal lengths of the two cameras are different and each camera is able to rotate independently. A single closed form solution is obtained for all models. The influence of the stereo camera model to the field of view, occlusion, and search area used for matching is shown in this paper. And errors due to inaccurate focal length are analyzed and simulation results are shown. It is expected that the three dimensional locations of objects are determined in real time by applying proposed stereo camera models to the active stereo vision system, such as a mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.361-364
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• 1997

There has been requested to automate the welding process in shipyard due to its dependence on skilled operators and the inferior working environments. According to these demands, multiple robot welding system for sub-assembly welding line has been developed, realized and installed at Keoje Shipyard. In order to realize automatic welding system, robots have to be equipped with the sensing system to recognize the position of the welding panels. In this research, a camera vision system is developed to detect the position of base panels for subassembly line in shipbuilding. Two camera vision systems are used in two different stages (Mounting and Welding) to automate the recognition and positioning of welding lines. For automatic recognition of panel position, various image processing algorithms are proposed in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.87-98
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• 1999

This study is concentrated on the development of real-time estimation model and vision control method as well as the experimental test. The proposed method permits a kind of adaptability not otherwise available in that the relationship between the camera-space location of manipulable visual cues and the vector of manipulator joint coordinates is estimate in real time. This is done based on a estimation model ta\hat generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation as well as uncertainty of manipulator. This vision control method is roboust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the manipulator, and correct knowledge of position and orientation of CCD camera with respect to the manipulator base. Finally, evidence of the ability of real-time vision control method for manipulator's position control is provided by performing the thin-rod placement in space with 2 cues test model which is completed without a prior knowledge of camera or manipulator positions. This feature opens the door to a range of applications of manipulation, including a mobile manipulator with stationary cameras tracking and providing information for control of the manipulator event.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.216-220
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• 2007

Camera calibration in machine vision is the process of determining the intrinsic camera parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1836-1839
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• 1997

This paper presents machine vision technique with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.179-185
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• 1997

This paper presents machine vision technique with a camera modeling that accounts for major sources of camera distortion, namely,radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to varios degrees of decentering,that is,the optical centers of lens elements are not strictly collinear. Thin prism distortion arises form imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of and to apply the line of part manufacturing.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.803-811
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• 2002

Machine vision systems are usually used to identify traffic lanes and then determine the steering angle of an autonomous vehicle in real time. The steering angle is calculated using a geometric model of various parameters including the orientation, position, and hardware specification of a camera in the machine vision system. To find the accurate values of the parameters, camera calibration is required. This paper presents a new camera-calibration algorithm using known traffic lane features, line thickness and lane width. The camera parameters considered are divided into two groups: Group I (the camera orientation, the uncertainty image scale factor, and the focal length) and Group II(the camera position). First, six control points are extracted from an image of two traffic lines and then eight nonlinear equations are generated based on the points. The least square method is used to find the estimates for the Group I parameters. Finally, values of the Group II parameters are determined using point correspondences between the image and its corresponding real world. Experimental results prove the feasibility of the proposed algorithm.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.64-72
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• 1998

This paper a new approach to the design of machine vision technique with a camera modeling that accounts for major sources of geometric distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering , that is , the optical centers of lens design and manufacturing as well as camera assembly. It is our propose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed vision system is illustrated by simulation and experiment.

• Journal of the Korean Institute of Navigation
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• v.16 no.3
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• pp.77-85
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• 1992

Camera arrangement for depth and image correspondence is very important to the computer vision. Two conventional comera arrangements for stereo computer vision are lateral model and axial motion model. In this paper, using the axial motion stereo camera model, the algorithm for camera focal length measurement and the surface smoothness with the radiance-irradiance is proposed fro 3-dimensional image correspondence on stereo computer vision. By adapting the above algorithm, camera focal length can be measured precisely and the resolution of 3-dimensional image correspondence has been improved comparing to that of the axial motion model without the radiance-irradiance relation.

• 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.