• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.509-523
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• 2016

The soil prediction can provide quantitative soil information for sustainable mountainous ecosystem management. Visible near infrared spectroscopy, one of soil prediction methods, has been applied to predict several soil properties with effective costs, rapid and nondesctructive analysis, and satisfactory accuracy. Spectral preprocessing is a essential procedure to correct noisy spectra for visible near infrared spectroscopy. However, there are no attempts to evaluate various spectral preprocessing methods. We tested 5 different pretreatments, namely continuum removal, Savitzky-Golay filter, discrete wavelet transform, 1st derivative, and 2nd derivative to predict soil carbon(C) and nitrogen(N). Partial least squares regression was used for the prediction method. The total of 153 soil samples was split into 122 samples for calibration and 31 samples for validation. In the all range, absorption was increased with increasing C contents. Specifically, the visible region (650nm and 700nm) showed high values of the correlation coefficient with soil C and N contents. For spectral preprocessing methods, continuum removal had the highest prediction accuracy(Root Mean Square Error) for C(9.53mg/g) and N(0.79mg/g). Therefore, continuum removal was selected as the best preprocessing method. Additionally, there were no distinct differences between Savitzky-Golay filter and discrete wavelet transform for visual assessment and the methods showed similar validation results. According to the results, we also recommended Savitzky-Golay filter that is a simple pre-treatment with continuum removal.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.10
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• pp.1050-1060
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• 2009

In this paper, a X-Band T/R-module for SAR(Synthetic Aperture Radar) systems based on active phased array antennas is designed and fabricated. The T/R modules have a and width of more than 800 MHz centered at X-Band and support dual, switched polarizations. The output power of the module is 7 watts over a wide bandwidth. The noise figure is as low as 3.9 dB. Phase and amplitude are controlled by a 6-bit phase shifter and a 6-bit digital attenuator, respectively. Further the fabricated T/R module has est and calibration port with directional coupler and power divider. Highly integrated T/R module is achieved by using LTCC(Low Temperature Co-fired Ceramic) multiple layer substrate. RMS gain error is less than 0.8 dB max. in Rx mode, and RMS phase error is less than $4^{\circ}$ max. in Rx/Tx phase under all operating frequency band, or the T/R module meet the required electrical performance m test. This structure an be applied to active phase array SAR Antennas.

• Journal of the Korean earth science society
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• v.33 no.7
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• pp.596-607
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• 2012

The R-Z relationship is one of important error factors to determine the accuracy of radar rainfall estimation. In this study, we have explored the effect of the R-Z relationships derived from disdrometer data in estimating the radar rainfall. The heavy rain event that produced flooding in St-Remi, Quebec, Canada has been occurred. We have tried to investigate the severity of rain for this event using high temporal (2.5 min) and spatial resolution ($1^{\circ}$ by 250 m) radar data obtained from the McGill S-band radar. Radar data revealed that the heavy rain cells pass directly over St-Remi while the coarse raingauge network was not sufficient to detect this rain event. The maximum 30 min (1 h) accumulation reaches about 39 (42) mm in St-Remi. During the rain event, the two disdrometers (POSS; Precipitation Occurrence Sensor System) were available: One used for the reflectivity calibration by comparing disdrometer Z and radar Z and the other for deriving disdrometric R-Z relationships. The result shows the significant improvement with the disdrometric reflectivity-dependent R-Z relationships against the climatological R-Z relationship. The bias in radar rain estimation is reduced from +12% to -2% and the root-mean squared error from 16 to 10% for daily accumulation. Using the estimated radar rainfall rate with disdrometric R-Z relationships, the flood event was well captured with proper timing and amount.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.144-150
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• 2019

In this study, resistance spot welding was performed using a high tensile steel plate SGAFC 780. The shear tensile strength, fracture profile, nugget diameter, and simulation were compared according to the conditions. After the nugget diameter calibration, the minimum diameter of welding was more than 4.3mm when the welding current was 8kVA or more. At 9kVA and above 10kVA, the minimum nugget diameter of 4.3mm was satisfied. On the other hand, due to the high current and time, the fly phenomenon occurred and the deep indentation remained. An evaluation of the weldability confirmed that there was an interval that was evaluated as weld failure due to the creep phenomenon, which satisfied the tensile shear strength and minimum nugget diameter. On the other hand, areas that have sufficient load bearing capacity even when drift has occurred were also identified. The simulation results show that the error rate was less than 4.2% when comparing the nugget diameter in the simulation and the experimental results in the appropriate weld zone, and confirmed the reliability of the simulation.

• Journal of Bio-Environment Control
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• v.24 no.3
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• pp.210-216
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• 2015

Purpose of this study was a development of an image processing algorithm to recognize paprika and acquire it's 3D coordinates from stereo images to precisely control an end-effector of a paprika auto harvester. First, H and S threshold was set using HSI histogram analyze for extracting ROI(region of interest) from raw paprika cultivation images. Next, fundamental matrix of a stereo camera system was calculated to process matching between extracted ROI of corresponding images. Epipolar lines were acquired using F matrix, and $11{\times}11$ mask was used to compare pixels on the line. Distance between extracted corresponding points were calibrated using 3D coordinates of a calibration board. Non linear regression analyze was used to prove relation between each pixel disparity of corresponding points and depth(Z). Finally, the program could calculate horizontal(X), vertical(Y) directional coordinates using stereo camera's geometry. Horizontal directional coordinate's average error was 5.3mm, vertical was 18.8mm, depth was 5.4mm. Most of the error was occurred at 400~450mm of depth and distorted regions of image.

• Asian Journal of Turfgrass Science
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• v.23 no.1
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• pp.77-90
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• 2009

Near Infrared Reflectance Spectroscopy(NIRS) is a quick, accurate, and non-destructive method to measure multiple nutrient components in plant leaves. This study was to acquire a liner regression equation by evaluating the nutrient contents of 'CY2' creeping bentgrass rapidly and accurately using NIRS. In particular, nitrogen fertility is a primary element to keep maintaining good quality of turfgrass. Nitrogen, moisture, carbohydrate, and starch were assessed and analyzed from 'CY2' creeping bentgrass clippings. A linear regression equation was obtained from accessing NIRS values from NIR spectrophotometer(NIR system, Model XDS, XM-1100 series, FOSS, Sweden) programmed with WinISI III project manager v1.50e and ISIscan(R) (Infrasoft International) and calibrated with laboratory values via chemical analysis from an authorized institute. The equation was formulated as MPLS(modified partial least squares) analyzing laboratory values and mathematically pre-treated spectra. The accuracy of the acquired equation was confirmed with SEP(standard error of prediction), which indicated as correlation coefficient($r^2$) and prediction error of sample unacquainted, followed by the verification of model equation of real values and these monitoring results. As results of monitoring, $r^2$ of nitrogen, moisture, and carbohydrate in 'CY2' creeping bentgrass was 0.840, 0.904, and 0.944, respectively. SEP was 0.066, 1.868, and 0.601, respectively. After outlier treatment, $r^2$ was 0.892, 0.925, and 0.971, while SEP was 0.052, 1.577, and 0.394, respectively, which totally showed a high correlation. However, $r^2$ of starch was 0.464, which appeared a low correlation. Thereof, the verified equation appearing higher $r^2$ of nitrogen, moisture, and carbohydrate showed its higher accuracy of prediction model, which finally could be put into practical use for turf management system.

• Journal of the Korean Society of Radiology
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• v.9 no.7
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• pp.425-431
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• 2015

Measurement accuracy was evaluated for the respiratory air flow transducer developed for applications under emergent situations. Pressure-Flow calibration equation was obtained by acquisition of air flow signals from the transducer in response to 6 flow waveforms, similar to those of artificial ventilation, generated by the standard flow generator system. Tidal volume and maximal flow rate were calculated on the flow signal then compared with the error-free data obtained by the linear displacement transducer of the flow generator system. Mean relative error of the tidal volume was within 3% and that of the maximal flow rate, approximately 5%, demonstrating accurate enough measurements. Therefore, the transducer could be applied to emergent situations to monitor the respiratory air flow signal as well as diagnostic parameters in real time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.113-120
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• 2005

3D reconstruction of a scene structure from un-calibrated image sequences has been long one of the central problems in computer vision. For 3D reconstruction in Euclidean space, projective reconstruction, which is classified into the merging method and the factorization, is needed as a preceding step. By calculating all camera projection matrices and structures at the same time, the factorization method suffers less from dia and error accumulation than the merging. However, the factorization is hard to analyze precisely long sequences because it is based on the assumption that all correspondences must remain in all views from the first frame to the last. This paper presents a new projective reconstruction method for recovery of 3D structure over long sequences. We break a full sequence into sub-sequences based on a quantitative measure considering the number of matching points between frames, the homography error, and the distribution of matching points on the frame. All of the projective reconstructions of sub-sequences are registered into the same coordinate frame for a complete description of the scene. no experimental results showed that the proposed method can recover more precise 3D structure than the merging method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.537-546
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• 2019

The paper actualizes the twin camera module system that is portable and very useful for the production of 3D contents. The suggested twin camera module system is a system to be able to display the 3D image after converting the inputted image from 2D stereo camera. To evaluate the performance of the twin camera module suggested in this paper, I assessed the correction of Rotation and Tilt created depending on the visual difference between the left and right stereoscopic image shot by the left and right lenses by using the Test Platform. In addition, I verified the efficiency of the twin camera module system through verifying Depth Error of 3D stereoscopic image by means of Scale Invariant Feature Transform(SIFT) algorithm. I think that if the user utilizes the suggested twin camera module system in displaying the image to the external after converting the shot image into the 3D stereoscopic image and the preparation image, it is possible to display the image in a matched way with an output device fit respectively for different 3D image production methods and if the user utilizes the system in displaying the created image in the form of the 3D stereoscopic image and the preparation image via different channels, it is possible to produce 3D image contents easily and conveniently with applying to lots of products.