• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.96-98
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• 2005

In this paper, an algorithm to compensate the distorted signals due to Current Transformer(CT) saturation is suggested, First, DWT which can be easily realized by filter banks in real-time applications is used to detect a start point and an end point of the saturation. Secondly, For enough Datas those need to use the least-square curve fitting method, the distorted current signal is compensated by the AR(autoregressive) model using the data during the previous healthy section until pick point of Saturation. Thirdly, the least-square curve fitting method is used to restore the distorted section of the secondary current. Finaly, this algorithm had a Hadware test using DSP board(TMS320C32) with Doble test device. DWT has superior detection accuracy and the proposed compensation algorithm which shows very stable features under various levels of remanent flux in the CT core is also satisfactory. And this algorithm is more correct than a previous algorithm which is only using the LSQ fitting method. Also it can be used as a MU involving the compensation function that acquires the second data from CT and PT.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.571-575
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• 2003

In this paper, we describe a method for fuzzy polynomial regression analysis for fuzzy input--output data using shape preserving operations for least-squares fitting. Shape preserving operations simplifies the computation of fuzzy arithmetic operations. We derive the solution using mixed nonlinear program.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.163-168
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• 2011

In this paper, we proposed non-linear gamma curve algorithm for gamma correction. The previous non-linear gamma curve algorithm is generated by the least square polynomial using the Gauss-Jordan inverse matrix. However, the previous algorithm has some weak points. When calculating coefficients using inverse matrix of higher degree, occurred truncation errors. Also, only if input sample points are existed regular interval on 10-bit scale, the least square polynomial is accurately works. To compensate weak-points, we calculated accurate coefficients of polynomial using eigenvalue and orthogonal value of mat11x from singular value decomposition (SVD) and QR decomposition of vandemond matrix. Also, we used input data part segmentation, then we performed polynomial curve fitting and merged curve fitting results. When compared the previous method and proposed method using the mean square error (MSE) and the standard deviation (STD), the proposed segmented polynomial curve fitting is highly accuracy that MSE under the least significant bit (LSB) error range is approximately $10^{-9}$ and STD is about $10^{-5}$.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.415-419
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• 2008

Detecting and correcting defects on LCD glasses early in the manufacturing process becomes important for panel makers to reduce the manufacturing costs and to improve productivity. Many attempts have been made and were successfully applied to detect and identify simple defects such as scratches, dents, and foreign objects on glasses. However, it is still difficult to robustly detect low-contrast defect region, called Mura or blemish area on glasses. Typically, these defect areas are roughly defined as relatively large, several millimeters of diameter, and relatively dark and/or bright region of low Signal-to-Noise Ratio (SNR) against background of low-frequency signal. The aim of this article is to present a robust algorithm to segment these blemish defects. Early 90's, a highly robust estimator, known as the Model-Fitting (MF) estimator was developed by X. Zhuang et. al. and have been successfully used in many computer vision application. Compared to the conventional Least-Square (LS) estimator the MF estimator can successfully estimate model parameters from a dataset of contaminated Gaussian mixture. Such a noise model is defined as a regular white Gaussian noise model with probability $1-\varepsilon$ plus an outlier process with probability $varepsilon$. In the sense of robust estimation, the blemish defect in images can be considered as being a group of outliers in the process of estimating image background model parameters. The algorithm developed in this paper uses a modified MF estimator to robustly estimate the background model and as a by-product to segment the blemish defects, the outliers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.570-575
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• 2002

This paper presents a new circular curve fitting approach of articulated manipulators, based on pseudoinverses. The paper aims at gaining the interpolation of circle from n data points, under the condition that the fitted circle should pass both a start point and an end point. In this paper, two algorithms of circular interpolation are presented. Prior to circular interpolation, are a spherical fitting should be performed, using least squares. In the first algorithm, the relationship between point data and normal vector on the sphere is used. In the second algorithm. the equation of plane which can be obtained from 3 points, i.e., a start point, an end point, and center of a sphere. The proposed algorithms are show to be efficient by using MATLAB-based simulation.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.7
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• pp.149-154
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• 2001

This study discusses a non-contact optical technique, electronic speckle pattern interferometry(ESPI), that is well suited for a deformation measurement of structure. Phase shifting method and unwrapping method have used to make deformation quantitative widely. In this paper, a previous numerical formula for phase shifting method is reconstructed in addition to least square fitting method to improve sensitivity and phase unwrapping based on vertical-horizontal scanning method is applied to analyze in-plane and out-of-plane deformation quantitatively.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.171-178
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• 2001

The nonlinearity of a laser interferometer usually ranges from sub-nanometer to several manometers. This nonlinearity, which has periodic characteristics, limits the accuracy of the interferometer at the sub-nanometer level. The nonlinearity error of the one-frequency homodyne interferometer with quadrature fringe detection results from a number of factors including polarization mixing by imperfect optical elements, unequal gain of photo detectors, lack of quadrature between two signals and misalignment. In this paper, we described a method for measuring and compensating the nonlinearity of homodyne interferometer using the elliptical fitting technique with least-square method. Experimental results demonstrate that $^\pm$3.5 nm nonlinearity can be reduced to $^\pm$0.2 nm level.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.88-90
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• 2003

In this paper, an algorithm to compensate the distorted signals due to CT(Current Transformer) saturation is suggested. Firstly, WT(Wavelet Transform) is used to detect a start point and an end point of saturation. Filter banks which can be easily realized in real-time applications are employed in detecting CT saturation. Secondly, least-square curve fitting method is used to restore the distorted section of the secondary current. Fault simulations are performed on a power system model using EMTP(Electromagnetic Transient Program). A series of test results indicate that WT has superior detection accuracy and the proposed algorithm which shows very stable features under various levels of remanent flux is also satisfactory.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.153-158
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• 2008

This paper deals with the geometric fitting algorithms for parametric curves and surfaces in 2-D/3-D space, which estimate the curve/surface parameters by minimizing the square sum of the shortest distances between the curve/surface and the given points. We identify three algorithmic approaches for solving the nonlinear problem of geometric fitting. As their general implementation we describe a new algorithm for geometric fitting of parametric curves and surfaces. The curve/surface parameters are estimated in terms of form, position, and rotation parameters. We test and evaluate the performances of the algorithms with fitting examples.

• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.42-47
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• 2001

In this paper, we present a curve fitting algorithm using a ball curve. Our algorithm is recursive method for fitting, which is not a traditional ball function but a continuous ball function. This algorithm consists of two steps. The first step, it is classified the composite corner points to joint points until selected from the given data set. The second step is the curve fitting. The basis function for curve fitting is use to ball function. Also, the weighted least square method, to insert knot, is an efficient method for piecewise ball curve and ball curve segments will be smoothly connected at all composit points. The proposed algorithm will be applied to represent image representation, like fonts, digital image and GIS.