• Current Optics and Photonics
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• v.7 no.6
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• pp.701-707
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• 2023

In laser imaging, accurate extraction of the laser's center is essential. Several methods exist to extract the laser's center in an image, such as the geometric mean, the parabolic curve fitting, and the Gaussian curve fitting, etc. The Gaussian curve fitting is the most suitable because it is based on the physical properties of the laser. The width of the Gaussian laser beam depends on the distance from the laser source to the target object. It is assumed in general that the distance remains constant at a laser spot resulting in a symmetric Gaussian model for the laser image. However, on a curved surface of the object, the distance is not constant; The laser beam is narrower on the side closer to the focal point of the laser light and wider on the side closer to the laser source, which causes the distribution of the laser beam to skew. This study presents a modified Gaussian model in the laser imaging to incorporate the slant angle of a curved object. The proposed method is verified with simulation and experiments.

• Korean Journal of Optics and Photonics
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• v.17 no.3
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• pp.216-222
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• 2006

We propose the use of the Gaussian-curve fitting algorithm for the improvement of measurement accuracy in wavelengthscanned Fabry-Perot filter based demodulation systems. The peak locations of FBG sensors were calculated from the fitted curves rather than from distorted PD profiles, resulting in much better measurement accuracy than that of the highest-peak search algorithm. Also, the algorithm was proved to minimize measurement uncertainty of spectrally-distorted grating sensors. From our experimental results, a temperature resolution as small as ${\sim}0.3^{\circ}C$ was readily achieved by use of the Gaussian-curve fitting algorithm whereas the highest-peak search algorithm gave a temperature resolution larger than ${\sim}4^{\circ}C$.

• Journal of Korean Vacuum Science & Technology
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• v.3 no.2
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• pp.107-111
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• 1999

We developed the experimental function (ERF) which can be used for the numerical curve fitting analysis in photoelectron spectroscopy (PES). We selected the core-levels of Ag 3d5/2 and Au 4f7/2 to obtain the ERF from the measured core-level spectra. For the numerical fourier transformation we applied the fast transform (FFT) algorithm. we considered optical (Wiener) filtering with the FFT due to noise and used Hann window function to remedy the information leakage in frequency domain due to discrete and finite sampling of measurement. The comparison of the curve fitting results using the ERF obtained in this work and the mathematical response function with a gaussian in the conventional approach shows clearly the improvement of the curve fitting analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.913-917
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• 2013

During the restoration process of primary restorative transmission system, some over voltages may happen due to nonlinear interaction between unloaded transformers and transmission systems. These over voltages caused by harmonic resonance can be suppressed by inserting damping loads before energizing transformers. But it is very difficult to predict the occurrence possibility of harmonic resonance and complex simulation must be repeated to estimate the sufficient damping loads. This paper presents a damping loads prediction system to prevent harmonic resonance. Detailed analysis of the relationship between harmonic resonance and the amount of damping loads is discussed. The prediction system is developed using a curve fitting and a neural network based on this relationship. A curve fitting used a Gaussian function based on non-linear least square method and multi-layer back-propagation neural network is applied. The system is applied to primary restorative transmission lines in korean power system and the result showed satisfactory performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.33-39
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• 2018

An additive noise reduction algorithm for a mass spectrum analyzer is proposed. From the measured ion signal, we first used an estimated threshold from the mode of the measured signal to eliminate background noises with the white Gaussian characteristics. Also, a signal block corresponding to each mass index is constructed to perform a second order curve fitting and a linear approximation to signal block. In this process, the effective signal block composed of only the ion signal can be reconstructed by removing the impulsive noises and the sample signals which are insufficient to be viewed as normal ion signals. By performing curve fitting on the effective signal block, the noise-free mass spectrum can be obtained. To evaluate the performance of the proposed method, a simulation was performed using the signals acquired from the development equipment. Simulation results show the validity of the threshold setting from the mode and the superiority of the proposed curve fitting and linear approximation based noise canceling algorithm.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.878-887
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• 2005

The passive focusing method finds the in-focus position by analyzing images captured by a camera. In this paper, we propose an efficient passive auto-focusing algorithm for video measuring systems. The sum of modified Laplacian of Gaussian is used to calculate focus values from images and Gaussian curve fitting is applied to estimate the optimal in-focus position. The Proposed method is tested for various objects and illuminations. The test result is compared with other methods to verify accuracy and efficiency of the proposed algorithm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.3
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• pp.223-231
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• 2022

Spectroscopies are the most widely used for understanding the crystallographic, chemical, and physical aspects of materials; therefore, numerous commercial and non-commercial software have been introduced to help researchers better handling their spectroscopic data. However, not many researchers, especially early-stage ones, have a proper background knowledge on the choice of fitting functions and a technique for actual fitting, although the essence of such data analysis is peak fitting. In this regard, we present a practical guide for peak fitting for data analysis. We start with a basic-level theoretical background why and how a certain protocol for peak fitting works, followed by a step-by-step visualized demonstration how an actual fitting is performed. We expect that this contribution is sure to help many active researchers in the discipline of materials science better handle their spectroscopic data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.81-88
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• 2011

Mini Double Gears Frame is critical part of PDP and also produces couple hundred thousand every month. In the process of mass production, product inspection is very important process. Double Gear, one of the part of machine, was inspected by human eyes which caused mistakes and slow progress. To achieve the speed and accuracy the system was compensated by vision system which is inspecting automatically. The focus value is measured based on the fact that high contrast images have much high frequency edge information. High frequency term of the image is extracted using the high-pass filter and the sum of the high frequency term is used as the focus value. We used a Gaussian smoothing filter to reduce the noise and then measures the focus value using the modified Laplacian filter called a Sum modified Laplacian Focus values for the various lens positions are calculated and the position with the maximum focus value is decided as the focused position. The focus values calculated in various lens position showed the Gaussian distribution. We proposed a method to estimate the best focus position using the Gaussian curve fitting. Focus values of the uniform interval lens positions are calculated and the values are used to estimate the Gaussian distribution parameters to find the best focus position.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.9
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• pp.14-23
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• 1993

In this paper, we present analysis results of various intermodulation products (IMPs) evaluation methods previously proposed for nonlinear systems. The results indicate that out of these methods, Fuenzalida and Simbo's method is the best for efficient evaluation of IMPs. Also, we present a detailed mathematical analysis of IMP and show how to apply the equations related to IMP to actual program implementations with examples. In this paper, we newly introduce three methods to reduce the IMP calculation time and improve the accuracy of the outputs :1) TWTA curve fitting method by LS (Least Square), 2) IMP evaluation technique which is based on a look-up table 3) Gaussian spectral shaping for PSK signal instead of convolution. The IMP evaluation results obtained by the new approaches introduced in this paper resulted in a good match with the published outputs in the open literature and showed improved performance especially in the TWTA curve .

• ETRI Journal
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• v.27 no.2
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• pp.188-194
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• 2005

We report on the improvement of critical dimension (CD) linearity on a photomask by applying the concept of process proximity correction to a laser lithographic process used for the fabrication of photomasks. Rule-based laser process proximity correction (LPC) was performed using an automated optical proximity correction tool and we obtained dramatic improvement of CD linearity on a photomask. A study on model-based LPC was executed using a two-Gaussian kernel function and we extracted model parameters for the laser lithographic process by fitting the model-predicted CD linearity data with measured ones. Model-predicted bias values of isolated space (I/S), arrayed contact (A/C) and isolated contact (I/C) were in good agreement with those obtained by the nonlinear curve-fitting method used for the rule-based LPC.