• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.187-190
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• 2003

In this paper, we propose an extrinsic calibration method for a multi-view camera to get an optimal pose in 3D space. Conventional calibration algorithms do not guarantee the calibration accuracy at a mid/long distance because pixel errors increase as the distance between camera and pattern goes far. To compensate for the calibration errors, firstly, we apply the Tsai's algorithm to each lens so that we obtain initial extrinsic parameters Then, we estimate extrinsic parameters by using distance vectors obtained from structural cues of a multi-view camera. After we get the estimated extrinsic parameters of each lens, we carry out a non-linear optimization using the relationship between camera coordinate and world coordinate iteratively. The optimal camera parameters can be used in generating 3D panoramic virtual environment and supporting AR applications.

• Journal of Astronomy and Space Sciences
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• 제38권3호
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• pp.157-164
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• 2021

We describe a method for the in-orbit calibration of body-mounted magnetometers based on the CHAOS-7 geomagnetic field model. The code is designed to find the true calibration parameters autonomously by using only the onboard magnetometer data and the corresponding CHAOS outputs. As the model output and satellite data have different coordinate systems, they are first transformed to a Star Tracker Coordinate (STC). Then, non-linear optimization processes are run to minimize the differences between the CHAOS-7 model and satellite data in the STC. The process finally searches out a suite of calibration parameters that can maximize the model-data agreement. These parameters include the instrument gain, offset, axis orthogonality, and Euler rotation matrices between the magnetometer frame and the STC. To validate the performance of the Python code, we first produce pseudo satellite data by convoluting CHAOS-7 model outputs with a prescribed set of the 'true' calibration parameters. Then, we let the code autonomously undistort the pseudo satellite data through optimization processes, which ultimately track down the initially prescribed calibration parameters. The reconstructed parameters are in good agreement with the prescribed (true) ones, which demonstrates that the code can be used for actual instrument data calibration. This study is performed using Python 3.8.5, NumPy 1.19.2, SciPy 1.6, AstroPy 4.2, SpacePy 0.2.1, and ChaosmagPy 0.5 including the CHAOS-7.6 geomagnetic field model. This code will be utilized for processing NextSat-1 and Small scale magNetospheric and Ionospheric Plasma Experiment (SNIPE) data in the future.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1248-1250
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• 1996

The objective of camera calibration is to obtain the correlation between camera image coordinate and 3-D real world coordinate. Most calibration methods are based on the camera model which consists of physical parameters of the camera like position, orientation, focal length, etc and in this case camera calibration means the process of computing those parameters. In this research, we suggest a new approach which must be very efficient because the artificial neural network(ANN) model implicitly contains all the physical parameters, some of which are very difficult to be estimated by the existing calibration methods. Implicit camera calibration which means the process of calibrating a camera without explicitly computing its physical parameters can be used for both 3-D measurement and generation of image coordinates. As training each calibration points having different height, we can find the perspective projection point. The point can be used for reconstruction 3-D real world coordinate having arbitrary height and image coordinate of arbitrary 3-D real world coordinate. Experimental comparison of our method with well-known Tsai's 2 stage method is made to verify the effectiveness of the proposed method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1512-1517
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• 2003

This paper presents the calibration for the parallel typed tilting table. The calibration system needs only simple sensing device which is a digital indicator to measure the orientation of a table. The calibration algorithm is developed by a measurement operator. It eliminates the concern about the poor parameter observability due to a large number of parameters of parallel-mechanism. This paper uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of a observation matrix. The number of identifiable parameters is examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a Parallel-typed Tilting Table and all the necessary kinematic parameters are identifiable.

• 환경영향평가
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• 제20권3호
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• pp.357-365
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• 2011

The QUAL2K has the same basic characteristics as the QUAL2E model, which has been widely used in stream water quality modeling; in QUAL2K, however, various functions are supplemented. The QUAL2Kw model uses a genetic algorithm(GA) for automatic calibration of QUAL2K, and it can search for optimum water quality parameters efficiently using the calculation results of the model. The QUAL2Kw model was applied to the Gangneung Namdaecheon River on the east side of the Korean Peninsula. Because of the effluents from the urban area, the middle and lower parts of the river are more polluted than the upper parts. Moreover, the hydraulic characteristics differ between the lower and upper parts of rivers. Thus, the river reaches were divided into seven parts, auto-calibration for the multiple reaches was performed using the function of the user-defined automatic calibration of the rates worksheets. Because GA parameters affect the optimal solution of the model, the impact of the GA parameters used in QUAL2Kw on the fitness of the model was analyzed. Sensitivity analysis of various factors, such as population size, crossover probability, crossover mode, strategy for mutation and elitism, mutation rate, and reproduction plan, were performed. Using the results of this sensitivity analysis, the optimum GA parameters were selected to achieve the best fitness value.

• 한국측량학회지
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• 제32권3호
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• pp.205-216
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• 2014

Multi-camera systems have been widely used as cost-effective tools for the collection of geospatial data for various applications. In order to fully achieve the potential accuracy of these systems for object space reconstruction, careful system calibration should be carried out prior to data collection. Since the structural integrity of the involved cameras' components and system mounting parameters cannot be guaranteed over time, multi-camera system should be frequently calibrated to confirm the stability of the estimated parameters. Therefore, automated techniques are needed to facilitate and speed up the system calibration procedure. The automation of the multi-camera system calibration approach, which was proposed in the first part of this paper, is contingent on the automated detection, localization, and identification of the object space signalized targets in the images. In this paper, the automation of the proposed camera calibration procedure through automatic target extraction and labelling approaches will be presented. The introduced automated system calibration procedure is then implemented for a newly-developed multi-camera system while considering the optimum configuration for the data collection. Experimental results from the implemented system calibration procedure are finally presented to verify the feasibility the proposed automated procedure. Qualitative and quantitative evaluation of the estimated system calibration parameters from two-calibration sessions is also presented to confirm the stability of the cameras' interior orientation and system mounting parameters.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1082-1095
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• 2019

Camera calibration is an important part of machine vision and close-range photogrammetry. Since current calibration methods fail to obtain ideal internal and external camera parameters with limited computing resources on mobile terminals efficiently, this paper proposes an improved fast camera calibration method for mobile terminals. Based on traditional camera calibration method, the new method introduces two-order radial distortion and tangential distortion models to establish the camera model with nonlinear distortion items. Meanwhile, the nonlinear least square L-M algorithm is used to optimize parameters iteration, the new method can quickly obtain high-precise internal and external camera parameters. The experimental results show that the new method improves the efficiency and precision of camera calibration. Terminals simulation experiment on PC indicates that the time consuming of parameter iteration reduced from 0.220 seconds to 0.063 seconds (0.234 seconds on mobile terminals) and the average reprojection error reduced from 0.25 pixel to 0.15 pixel. Therefore, the new method is an ideal mobile terminals camera calibration method which can expand the application range of 3D reconstruction and close-range photogrammetry technology on mobile terminals.

• 한국농공학회논문집
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• 제59권2호
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• pp.19-27
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• 2017

Recently, the hydrological model Soil Water Assessment Tool (SWAT) has been applied in many watersheds in South Korea. This study estimated parameters in SWAT for calibrating streamflow in long-term drought periods. Therefore, we focused on the continuous severe drought periods 2014~2015, and understand the model calibrated parameters. The SWAT was applied to a $366.5km^2$ Gongdo watershed by using 14 years (2002~2015) daily observed streamflow (Q) including two years extreme drought period of 2014~2015. The 9 parameters of CN2, CANMX, ESCO, SOL_K, SLSOIL, LAT_TIME, GW_DELAY, GWQMN, ALPHA_BF were selected for model calibration. The SWAT result by focusing on 5 normal years (2002~2006) calibration showed the 14 years average Nash-Sutcliffe model efficiency (NSE) for Q and 1/Q with 0.78 and 0.58 respectively. On the other hand, the 14 years average NSEs of Q and 1/Q by focusing on 2 drought years (2014~2015) calibration were 0.86 and 0.76 respectively. Thus, we could infer that the SWAT calibration trial by focusing on drought periods data can be a good approach to calibrate both high flow and low flow by controlling the 9 drought affected parameters.

• 한국물환경학회지
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• 제40권4호
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• pp.179-194
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• 2024

Biophysicochemical processes in water environments and treatment systems have been great concerns of engineers and scientists for controlling the fate and transport of contaminants. These processes are practically formulated as mathematical models written in coupled differential equations. However, because these process-based mathematical models consist of a large number of model parameters, they are complicated in analytical or numerical computation. Users need to perform substantial trials and errors to achieve the best-fit simulation to measurements, relying on arbitrary selection of fitting parameters. Therefore, this study adopted a Bayesian calibration method to estimate best-fit model parameters in a systematic way and evaluated the applicability of the calibration method to biophysicochemical processes of water environments and treatment systems. The Bayesian calibration method was applied to the microbial growth-decay kinetics and flocculation kinetics, of which experimental data were obtained with batch kinetic experiments. The Bayesian calibration method was proven to be a reasonable, effective way for best-fit parameter estimation, demonstrating not only high-quality fitness, but also sensitivity of each parameter and correlation between different parameters. This state-of-the-art method will eventually help scientists and engineers to use complex process-based mathematical models consisting of various biophysicochemical processes.

• 한국정밀공학회지
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• 제16권2호통권95호
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• pp.164-175
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• 1999

If the camera plane is nearly parallel to the calibration board on which objects are defined, most of existing calibration approaches such as Tsai's radial-alignment-constraint method cannot be applied. Recently, for such an ill-conditioned case, Zhuang & Wu suggested the linear two-stage calibration algorithm assuming that the exact values of focal length and scale factor are known a priori. In this paper, we developed an iterative two-stage algorithm starts with initial guess fo the two parameters to determine the value of the others using Zhuang & Wu's method. In the second stage, the two parameters are locally optimized. This process is repeated until any improvement cannot be expected any more. The performance comparison between Zhuang & Wu's method and our algorithm shows the superiority of ours. Also included are the computational results for the effects of the distribution and the number of calibration points on the calibration performance.