• Near Infrared Analysis
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• v.2 no.1
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• pp.55-58
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• 2001

The object of this work was to investigate the influence of growing district and harvest year on calibration for sweetness (Brix) determination of Fuji apple fruit using near infrared (NIR) reflectance spectroscopy, and to develop the robust calibration across these variation. The calibration models was based on wavelength range of 1100∼2500 nm using a stepwise multiple linear regression. A calibration model by sample set of one growing district was not transferable to other growing districts. The combined calibration (data of three growing districts) predicted reasonable well against a population set drawn from all growing districts (SEP=0.69, Bias=0.075). A calibration model by sample set of one harvest year was not also transferable to other harvest years. The combined calibration (data of three harvest years) predicted well against a population set drawn from all harvest years (SEP=0.53, Bias=0.004).

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.649-659
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• 2018

The aim of this study is to develop a protocol for obtaining spectral signals that are robust to varying lighting conditions, which are often found in the Polar regions, for creating a spectral library specific to those regions. Because hyperspectral image (HSI)-derived spectra are collected on the same scale as images, they can be directly associated with image data. However, it is challenging to find precise and robust spectra that can be used for a spectral library from images taken under different lighting conditions. Hence, this study proposes a new radiometric calibration protocol that incorporates radiometric targets with a traditional vicarious calibration approach to solve issues in image-based spectrum measurements. HSIs obtained by the proposed method under different illumination levels are visually uniform and do not include any artifacts such as stripes or random noise. The extracted spectra capture spectral characteristics such as reflectance curve shapes and absorption features better than those that have not been calibrated. The results are also validated quantitatively. The calibrated spectra are shown to be very robust to varying lighting conditions and hence are suitable for a spectral library specific to the Polar regions.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.259-265
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• 2017

Magnetometer calibration must be performed before the use of three-axis magnetometers to ensure the accuracy of orientation estimation. Recently, one of the most popular calibration approaches is the ellipsoid fitting technique due to its high performance in calibration. To date, in fact, performances of the existing ellipsoid fitting methods have been evaluated with full range rotation data. However, in case of the calibration of magnetometers attached to vehicles, ships, and planes, it is very difficult to collect the full range rotation data since their allowable ranges in terms of roll and pitch are limited to small. This constraint may result in serious performance degradation of some ellipsoid fitting algorithms. Therefore, to be practical, this paper proposes a weighted least square-based magnetometer calibration method that is robust in roll-pitch limited conditions. Furthermore, the proposed method is a linear approach and thus is free from the well-known initial value issue in nonlinear approaches. Experimental results show the superiority of the proposed method to other ellipsoid-fitting calibration methods.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1614-1614
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• 2001

The sweetness (。Bix) of fruit is the main quality factor contributing to the fruit taste. The brix of the apple fruit can be measured non-destructively by near infrared (NIR) spectroscopy, allowing the sweetness grading of individual apple fruit. However, the fruit quality is influenced by various factors such as growing location, producing year, variety and harvest time etc., accordingly the robust NIR calibration is required. In this experimental results are presented the influence of two variations such as growing location and producing year of apple fruit in establishing of calibrations for sweetness, and developed a stable and highly accurate calibration. Apple fruit (Fuji) was collected every year from 1995 to 1997 in 3 different growing locations (Andong, Youngchun and Chungsong) of Kyungpook in Korea. NIR reflectance spectra of apple fruit were scanned in wavelength range of 1100∼2500nm using an InfraAlyzer 500C (Bran+Luebbe) with halogen lamp and PbS detector. The multiple linear regression and stepwise was carried out between the NIR raw spectra and the brix measured by refractometer to select the best regression equations. The calibration models by each growing district were well predicted to dependent sample set, but poorly predicted to independent sample set. Combined calibration model using data of three growing districts predicted reasonable well to a population set drawn from all growing districts(SEP = 0.69%, Bias=-0.075). The calibration models by each harvest year were not transferable across harvest year, however a combined calibration model using data of three harvest years was sufficiently robust to predict each sample sets(SEP = 0.53%, Bias = 0.004).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1191-1191
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• 2001

Generation of precise, accurate, and robust calibration models for spectroscopic methods of analysis can be time-consuming, expensive, and sometimes difficult to achieve. For these reasons, efforts have been made to find ways in which the calibration from one instrument can be moved to another with minimal performance reduction. A slight shift in nomenclature from the common term calibration transfer to the term calibration transport is used here to help resolve the subtle difference between two means of moving a calibration from one instrument to another. The former term denotes a transfer procedure that includes mathematical manipulation of the calibration data via some determined transfer function, whereas the latter term does not. Todays generation of process and laboratory FTNIR analyzers is capable of not only achieving calibration transfer, but also calibration transport often without the need of slope or bias adjustments. Several studies are used to examine the boundaries of the extent to which calibration transport is achieved in the refining industry. Data collected on multiple on-line and laboratory FTNIR analyzers located in multiple countries are considered, and the ultimate limitations discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.752-757
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• 2003

Recently, 3D structure recovery through self-calibration of camera has been actively researched. Traditional calibration algorithm requires known 3D coordinates of the control points while self-calibration only requires the corresponding points of images, thus it has more flexibility in real application. In general, self-calibration algorithm results in the nonlinear optimization problem using constraints from the intrinsic parameters of the camera. Thus, it requires initial value for the nonlinear minimization. Traditional approaches get the initial values assuming they have the same intrinsic parameters while they are dealing with the situation where the intrinsic parameters of the camera may change. In this paper, we propose new initialization method using the minimum 2 images. Proposed method is based on the assumption that the least violation of the camera’s intrinsic parameter gives more stable initial value. Synthetic and real experiment shows this result.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.265-277
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• 1999

Classical and inverse estimation methods are two well known methods in statistical calibration problems. When there are outliers, both methods have large MSE's and could not estimate the input value correctly. We suggest median calibration estimation based on the LD-statistics. To investigate the robust performances, the influence function of the median calibration estimator is calculated and compared with other methods. When there are outliers in the response variables, the influence function is found to be bounded. In simulation studies, the MSE's for each calibration methods are compared. The estimated inputs as well as the performance of the influence functions are calculated.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.1
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• pp.134-143
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• 2008

The hardware scatters as well as the engine parameters calibration have strong influences on exhaust emissions in recent diesel engines. In this research DoE(Design of Experiments) optimizations were done to study the possibility of minimizing the emission deviations caused by flow rate scatters of the injectors. It has been shown that the optimization of engine calibration, which minimizes the emission deviations, is feasible by establishing a target function representing the emission deviations for test results of maximum, mean and minimum flow rate injectors. It has also been shown that optimization of both emission deviations and emission level is possible by sequential DoE optimizations of the target functions representing the emission level and the emission deviations respectively with the appropriate boundary limits.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1457-1460
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• 2013

We propose a flexible camera calibration system for mobile platform to calibrate the camera's intrinsic parameters which based on the geometrical property of the vanishing points determined by two perpendicular groups of parallel lines. The system only requires the camera to observe a rectangle card show at a few(at least four)different orientation. The experimental results of the real images show the proposed calibration system in this paper is easy to use and robust.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.592-594
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• 2004

Camera calibration is an important problem to determine the relationship between 3D real world and 2D camera image. The existing calibration methods can be classified into linear and non-linear models. The linear methods are simple and robust against noise, but the accuracy expectation is generally poor. In comparison, if the non-linearity, which is due mainly to lens distortion, is corrected, the accuracy can be better. However, as the optical features of lens are diverse, no non-linear method can be always effective for diverse vision systems. In this paper, we propose a new approach to correct the calibration error of a linear method using GMDH algorithm. The proposed technique is simple in concept and showed improved accuracy in various cases.