• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.65-69
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• 1997

This paper presents a new approach to the calibration of a SCARA robot orientation 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. Thin prism distortion arises from 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 parts and to apply the line of manufacturing.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.117-121
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• 2001

This paper presents a new approach to the calibration of a SCARA robot orientation 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. Thin prism distortion arises from 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 parts and to apply the line of manufacturing.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.140-149
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• 2016

For visual measurement under dynamic scenarios, a zoom lens camera is more flexible than a fixed one. However, the challenges of distortion prediction within the whole focal range limit the widespread application of zoom lens cameras greatly. Thus, a novel sequential distortion correction method for a zoom lens camera is proposed in this study. In this paper, a distortion assessment method without coupling effect is depicted by an elaborated chessboard pattern. Then, the appropriate distortion correction model for a zoom lens camera is derived from the comparisons of some existing models and methods. To gain a rectified image at any zoom settings, a global distortion correction modeling method is developed with bundle adjustment. Based on some selected zoom settings, the optimized quadratic functions of distortion parameters are obtained from the global perspective. Using the proposed method, we can rectify all images from the calibrated zoom lens camera. Experimental results of different zoom lens cameras validate the feasibility and effectiveness of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.27-33
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• 2003

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, we propose the image-based, 3D modeling system using calibrated stereo cameras. The proposed algorithm for rendering, 3D model consists of three steps, camera calibration, 3D reconstruction, and 3D registration step. In the camera calibration step, we estimate the camera matrix for the image aquisition camera. In the 3D reconstruction step, we calculate 3D coordinates using triangulation from corresponding points of the stereo image. In the 3D registration step, we estimate the transformation matrix that transforms individually reconstructed 3D coordinates to the reference coordinate to render the single 3D model. As shown the result, we generated relatively accurate 3D model.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1162-1164
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• 2003

The methods of the geometric reconstruction and sensor calibration of satellite linear pushbroom images are investigated. The model of the sensor used is based on the SPOT model that is developed by Kraiky. The satellite trajectory is a Keplerian trajectory in the approximation. Four orbit parameters, longitude of the ascending node(${\omega}$), inclination of the orbit plan(I), latitude argument of the satellite(W) and distance between earth center and satellite, are used for the camera modeling. Time-dependent orbit parameters are expressed by quadratic polynomials. SPOT-5 images have been used for validation tests. The results are that the RMSE acquired from 20 GCPs is 1.763m and the RMSE of 5 checking points 2.470m. Because the ground resolution of SPOT-5 is 2.5m, the result obtained in this study has a good accuracy. It demonstrates that the sensor model developed by this study can be used to reconstruct the geometry of satellite image using pushbroom camera.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.543-547
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• 2002

In this paper, we introduce a more improved camera modeling method for linear pushbroom images than the method proposed by Orun and Natarajan(ON). ON model shows an accuracy of within 1 pixel if more than 10 ground control points(GCPs) are provided. In general, there is high correlation between platform position and attitude parameters but ON model ignores attitude variation in order to overcome such correlation. We propose a new method that obtains an optimal solution set of parameters without ignoring the attitude variation. We first assume that attitude parameters are constant and estimate platform position's. Then we estimate platform attitude parameters using the values of estimated position parameters. As a result, we can set up an accurate camera model for a linear pushbroom satellite scene. In particular, we can apply the camera model to its surrounding scenes because our model provide sufficient information on satellite's position and attitude not only for a single scene but also for a whole imaging segment. We tested on two images: one with a pixel size 6.6m$\times$6.6m acquired from EOC(Electro Optical Camera), and the other with a pixel size 10m$\times$l0m acquired from SPOT. Our camera model procedures were applied to the images and gave satisfying results. We had obtained the root mean square errors of 0.5 pixel and 0.3 pixel with 25 GCPs and 23 GCPs, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.344-352
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• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1164-1171
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• 2009

This paper proposes an efficient implementation way of traditional wooden building using Parametric modeling method which uses the relations of numerical value ratio between building materials. Building structures and order of construction for Geunjungjeon of Kyuungbok Palace is digitally implemented proving the efficiency of the suggested proposal. Although the existing digital modeling methods for traditional wooden building emphasize the exterior modeling of the building, our modeling method constructed numerous wooden materials and arranged those pieces orderly so that people can see the interior structures of the building which usually is beyond one's vision. The suggested Parametric modeling method, Multi-Object Texture Mapping, Physical Camera Restoration, and GI Renderer for implementing Geunjungjeon of Kyuungbok Palace can be practically used for digital implementation for other traditional wooden buildings.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.516-516
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• 2002

With the wide usage of LiDAR data and high-resolution satellite image, 3D modeling of buildings in urban areas has become an important research topic in the photogrammetry and computer vision field for many years. However the previous modeling has its limitations of merely texturing the image to the DSM surface of the study area and does not represent the relief of building surfaces. This study is focused on presenting a system of realistic 3D building modeling from consecutive stereo image sequences using digital camera. Generally when acquiring images through camera, various parameters such as zooming, focus, and attitude are necessary to extract accurate results, which in certain cases, some parameters have to be rectified. It is, however, not always possible or practical to precisely estimate or rectify the information of camera positions or attitudes. In this research, we constructed the collinearity condition of stereo images through extracting the distinctive points from stereo image sequence. In addition, we executed image matching with Graph Cut method, which has a very high accuracy. This system successfully performed the realistic modeling of building with a good visual quality. From the study, we concluded that 3D building modeling of city area could be acquired more realistically.