• 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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• 2003.10a
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• pp.250-255
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• 2003

The position of a 3-dimensional(3D) point can be measured by using calibrated stereo camera. To obtain more accurate measurement ,more accurate camera calibration is required. There are many existing methods to calibrate camera. The simple linear methods are usually not accurate due to nonlinear lens distortion. The nonlinear methods are accurate more than linear method, but it increase computational cost and good initial guess is needed. The multi step methods need to know some camera parameters of used camera. Recent years, these explicit model based camera calibration work with the development of more precise camera models involving correction of lens distortion. But these explicit model based camera calibration have disadvantages. So implicit camera calibration methods have been derived. One of the popular implicit camera calibration method is to use neural network. In this paper, we propose implicit stereo camera calibration method for 3D reconstruction using support vector machine. SVM can learn the relationship between 3D coordinate and image coordinate, and it shows the robust property with the presence of noise and lens distortion, results of simulation are shown in section 4.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1814-1819
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• 2004

The purpose of this research is to improve the reliability of automobile navigation system that utilizes the magnetic compass for localization. On account of its sensitiveness against the dynamic external interference of the magnetic field, the electronic compass itself is not accurate enough to be used for the localization compared to the gyro-compass. To overcome this shortcoming, in this research, a robust electronic compass is designed by using two magnetic compasses to cancel out the dynamic interferences efficiently. That is, a dual compass predictive calibration algorithm against irregular external interference of magnetic field is newly proposed and implemented in this paper. When the dynamic interference can be eliminated from the electronic compass, it becomes much accurate than the gyro-based system that suffers from the accumulative drift error. The reliability and performance of the designed system have been verified through the real driving experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.27-33
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• 2005

The purpose of this research is to improve the reliability of automobile navigation system that utilizes the magnetic compass for localization. On account of its sensitiveness against the dynamic external interference of the magnetic field, the electronic compass itself is not accurate enough to be used for the localization compared to the gyro-compass. To overcome this shortcoming, in this research, a robust electronic compass is designed by using two magnetic compasses to cancel out the dynamic interences efficiently. That is, a dual compass predictive calibration algorithm against irregular external interference of magnetic field is newly proposed and implemented in this paper. When the dynamic interference can be eliminated from the electronic compass, it becomes much accurate than the gyro-based system that suffers from the accumulative drift error. The reliability and performance of the designed system have been verified through the real driving experiments.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2000.06a
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• pp.48-48
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• 2000

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2005.02a
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• pp.141-149
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• 2005

• Journal of The Korean Astronomical Society
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• v.39 no.4
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• pp.151-155
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• 2006

Long slit spectrometers are widely used in optical and infrared bands in astronomy. Absolute flux calibration for extended sources, however, is not straightforward, because a portion of the radiation energy from a flux calibration star is blocked by the narrow slit width. Assuming that the point spread function(PSF) of the star is circularly symmetric, we develop a robust method to extrapolate the detected stellar flux to the unobscured flux using the measured PSF along the slit-length direction. We apply this method to our long slit data and prove that the uncertainty of the absolute flux calibration is less than a few percents.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.191-200
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• 2017

A robust parameter set (ROPS) selection framework for an unsteady flow model was developed by combining Pareto optimums obtained by outcomes of model calibration using multi-site observations with the minimax regret approach (MRA). The multi-site calibration problem which is a multi-objective problem was solved by using an aggregation approach which aggregates the weighted criteria related to different sites into one measure, and then performs a large number of individual optimization runs with different weight combinations to obtain Pareto solutions. Roughness parameter structure which can describe the variation of Manning's n with discharges and sub-reaches was proposed and the related coefficients were optimized as model parameters. By applying the MRA which is a decision criterion, the Pareto solutions were ranked based on the obtained regrets related to each Pareto solution, and the top-rated one due to the lowest aggregated regrets of both calibration and validation was determined as the only ROPS. It was found that the determination of variable roughness and the corresponding standardized RMSEs at the two gauging stations varies considerably depending on the combinations of weights on the two sites. This method can provide the robust parameter set for the multi-site calibration problems in hydrologic and hydraulic models.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.54 no.1
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• pp.29-35
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• 2009

The aim of the present study was to update the calibration that is used for the measurement of the total nitrogen content in the rice plant samples by using the visible and near infrared spectrum. Before the equation merge, correlation coefficient of calibration equation for nitrogen content on each rice parts was 0.945 (Leaf), 0.928 (Stem), and 0.864 (Whole plant), respectively. In the calibration models created by each part in the rice plant under the various regression method, the calibration model for the leaf was recorded with relatively high accuracy. Among of those, the calibration equation developed by Partial least squares (PLS) method was more accurate than the Multiple linear regression (MLR) method. The calibration equation was sensitive based on variety and location variations. However, we have merged and enlarged various of the samples that made not only to measure the nitrogen content more accurately, but also later sampling populations became more diversified. After merging, $R^2$ value becomes more accurate and significantly to 0.950 (L.), 0.974 (S.), 0.940 (W.). Also, after removal of outlier, R2 values increased into 0.998, 0.995, and 0.997. In view of the results so far achieved, Standard error of prediction (SEP) and SEP (C) were reduced in the stem and whole plant. Biases were reduced in the leaf, stem as well as whole plant. Slopes were high in the stem. Standard deviation reduced in the stem but $R^2$ was high in the stem and whole plant. Result was indicated that calibration equation make update, and updating robust calibration equation from merge function and multi-variate calibration.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1615-1620
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• 2003

Kinematic calibration is a process whereby the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. Measuring all components of Cartesian posture, particularly the orientation, can be difficult. With partial pose measurements, all parameters may not be identifiable. This paper proposes a new device that can identify all kinematic parameters with partial pose measurements. Study is performed for a six degree-of-freedom fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector's motion to five degree-of-freedom and can measure position of the end-effector and one of its rotations. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise. Intrinsic inaccuracies of the device can significantly deteriorate the calibration results. A measurement procedure is proposed and formulations of cost functions are discussed to prevent propagation of the inaccuracies to the calibration results.