• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권3호
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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.

• 한국작물학회지
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• 제54권1호
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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.

• 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.

• 한국농공학회지
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• 제45권4호
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• pp.89-97
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• 2003

Using inference models developed for estimation of the parameters necessary to implement the Runoff Block of the Stormwater Management Model (SWMM), a number of alternative inference scenarios were developed to assess the influence of inference model complexity and structure on the calibration of the catchment modelling system. These inference models varied from the assumption of a spatially invariant value (catchment average) to spatially variable with each subcatchment having its own unique values. Fur-thermore, the influence of different measures of deviation between the recorded information and simulation predictions were considered. The results of these investigations indicate that the model performance is more influenced by model structure than complexity, and control parameter values are very much dependent on objective function selected as this factor was the most influential for both the initial estimates and the final results.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 봄 학술발표회 논문집
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• pp.559-566
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• 2000

본 연구에서는 비등방성 응력조건 하에서 콘 관입속도가 콘 관입시험 결과에 미치는 영향을 연구하기 위하여 유한요소해석 및 Calibration Chamber를 이용한 Miniature Piezocone의 관입시험이 수행되었으며 그 결과를 비교 분석하였다. 비등방성을 고려하기 위하여 Anisotropic Soil Model이 유한요소해석에 이용되었으며 LSU/CALCHAS(Louisiana State University Calibration Chamber System)가 Miniature Piezocone의 관입시험에 이용되었다. 콘 관입속도의 영향이외에도 OCR 및 필터위치의 영향을 고찰하였다.

• 한국농공학회논문집
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• 제51권1호
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• pp.1-9
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• 2009

The objective of this paper was to evaluate the auto-calibration with multi-objective optimization method to calibrate the parameters of the Soil and Water Assessment Tool (SWAT) model. The model was calibrated and validated by using nine years (1996-2004) of measured data for the 384-ha Baran reservoir subwatershed located in central Korea. Multi-objective optimization was performed for sixteen parameters related to runoff. The parameters were modified by the replacement or addition of an absolute change. The root mean square error (RMSE), relative mean absolute error (RMAE), Nash-Sutcliffe efficiency index (EI), determination coefficient ($R^2$) were used to evaluate the results of calibration and validation. The statistics of RMSE, RMAE, EI, and $R^2$ were 4.66 mm/day, 0.53 mm/day 0.86, and 0.89 for the calibration period and 3.98 mm/day, 0.51 mm/day, 0.83, and 0.84 for the validation period respectively. The statistical parameters indicated that the model provided a reasonable estimation of the runoff at the study watershed. This result was illustrated with a multi-objective optimization for the flow at an observation site within the Baran reservoir watershed.

• Bulletin of the Korean Chemical Society
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• 제22권3호
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• pp.251-252
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• 2001

• 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.

• 전자공학회논문지B
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• 제31B권2호
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• pp.56-68
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• 1994

The objective of camera calibration is to determine the internal optical characteristics of camera and the three-dimensional position and orientation of camera with respect to the real world. Calibration procedure for computer vision should be automatical, accurate and applicable to general purpose cameras and lenses. In this paper, we present camera calibration method which meets the above requirements. The algorithm is based on the two-stage method which takes into account lens distortion in the second stage. In this paper, the overdetermined nonlinear system is established in terms of the constraints to all directions and our calibration algorithm is proposed which is constructed by using Marquardt iterations and our calibration algorithm is proposed which is constructed by using Marquardt iteration method in solving nonlinear equations. Experimental results indicate that lens distortion should be taken into consideration for the calibration of the general-purpose lens. With 24 calibration points acquired out of 512$\times$512 image, the proposed algorithm came up with average error of less than 1 pixel and showed a higher accuracy over the conventional two-stage method.

• 반도체디스플레이기술학회지
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• 제2권4호
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• pp.23-26
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• 2003

The general users find difficulties in using ellipsometers. Thus, the object of this study is to construct an ellipsometer with simple operation principle. We developed an ellipsometer which does not require alignment and calibration before measuring sample. A basis structure model after rotating a compensator spectroscopic ellipsometry, the fixed incidence angle at $70^{\circ}$. This ellipsometer does not demand calibration, because the plane of incidence is not changed due to the novel sample holder structure. The results for various standard samples were compared with those from conventional RCSE to test the performance of this instrument. Also repeated measurements were performed to test the precision of the calibration coefficient in a plane of incidence fixed.