• Current Optics and Photonics
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• v.7 no.1
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• pp.38-46
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• 2023

Optical Fourier-domain reflectometry (OFDR) sensors have been widely used to measure distances with high resolution and speed in a noncontact state. In the electroplating process of a printed circuit board, it is critically important to monitor the copper-plating thickness, as small deviations can lead to defects, such as an open or short circuit. In this paper we employ a phase-based OFDR sensor for in situ relative distance sensing of a sample with nanometer-scale resolution, during electroplating. We also develop an optical-path difference (OPD)-regulated sensing probe that can maintain a preset distance from the sample. This function can markedly facilitate practical measurements in two aspects: Optimal distance setting for high signal-to-noise ratio OFDR sensing, and protection of a fragile probe tip via vertical evasion movement. In a sample with a centimeter-scale structure, a conventional OFDR sensor will probably either bump into the sample or practically out of the detection range of the sensing probe. To address this limitation, a novel OPD-regulated OFDR system is designed by combining the OFDR sensing probe and linear piezo motors with feedback-loop control. By using multiple OFDR sensors, it is possible to effectively monitor copper-plating thickness in situ and uniformize it at various positions.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.149-156
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• 2022

In this paper, it was attempted to form a titanium (Ti: Titanium) thin film using the atmospheric pressure plasma process technology for the conductor, which is the main component of the optical sensor. The atmospheric plasma equipment was remodeled. A 4-inch Ti target for sputter was etched using CF4 gas, and the by-product was coated on a glass sample. These by-products were formed up to about 2 cm, and could be divided into 15 areas according to color. Surface shape and constituent elements were analyzed using scanning electron microscopy (SEM) and energy dispersive spectrometer (EDS), respectively. Electrical properties using 4-point probe equipment were also measured. If the process is performed by positioning the sample at about 4.5 mm to 5 mm from the target, a uniform Ti thin film will be deposited. However, it was found that the thin film contained a significant amount of fluorine, which greatly affects the electrical properties of the thin film. Therefore, additional experiments and studies should be performed to remove or minimize fluorine during deposition.

• The Journal of Korean Academy of Prosthodontics
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• v.52 no.2
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• pp.97-104
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• 2014

This study was aimed to compare the radiopacity of four kinds of currently available resin based implant cements using digital radiography. Materials and Methods: Four resin-based implant cements((Estemp $Implant^{TM}$ (Spident, Incheon, Korea), $Premier^{(R)}$Implant (Premier, Pennsylvania, USA), $Cem-Implant^{TM}$ (B.J.M lab, Or-yehuda, Israel), $InterCem^{TM}$ (SCI-PHARM, California, USA)) and control group (Elite Cement $100^{TM}$ (GC, Tokyo, Japan) ) were mixed and cured according to the manufacturer's instructions on the custom made split-type metal mold. A total of 150 specimens of each cement were prepared and each specimen (purity over 99%) was placed side-by-side with an aluminum step wedge for image taking with Intraoral X-ray unit (Esx, Vatech, Korea) and digital X-ray sensor (EzSensor, Vatech, Korea). For the evaluation of aluminum wedge equivalent thickness (mm Al), ImageJ 1.47 m (Wayne Rasband, National Institutes of Health, USA) and Color inspector 3D ver 2.0 (Interaktive Visualisierung von Farbraumen, Berlin, Germany) programs were used. Result: Among the 5 cements, Elite cement $100^{TM}$ (control group) showed the highest radio-opacity in all thickness. In the experimental group, $InterCem^{TM}$ had the highest radio-opacity followed by $Premier^{(R)}$ Implant $Cement^{TM}$, $Cem-Implant^{TM}$ and Estemp $Implant^{TM}$. In addition, $InterCem^{TM}$ showed radio-opacity that met the ISO No. 4049 standard in all the tested specimen thickness. Cem-Implant on 0.5 mm thickness showed radiopacity that met the ISO No. 4049 standard. Conclusion: Among the implant resin-based cements tested in the study, $Premier^{(R)}$ Implant Cement and Estemp $Implant^{TM}$ did not show appropriate radio-opacity. Only $InterCem^{TM}$ and $Cem-Implant^{TM}$ 0.5 mm specimen had the proper radiopacity and met the experiment standard.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.63-73
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• 2007

This paper proposes an illuminant-adaptive reproduction method using light adaptation and flare conditions for a mobile display. Displayed images in daylight are perceived as quite dark due to the light adaptation of the human visual system, as the luminance of a mobile display is considerably lower than that of an outdoor environment. In addition, flare phenomena decrease the color gamut of a mobile display and de-saturating the chroma. Therefore, this paper presents an enhancement method composed of lightness enhancement and chroma compensation. First, the ambient light intensity is measured using a lux-sensor, then the flare is calculated based on the reflection ratio of the display device and the ambient light intensity. To improve the perceived image, the image's luminance is transformed by linearization of the response to the input luminance according to the ambient light intensity. Next, the displayed image is compensated according to the physically reduced chroma, resulting from flare phenomena. This study presents a color reproduction method based on an inverse cone response curve and flare condition. Consequently, the proposed algorithm improves the quality of the perceived image adaptive to an outdoor environment.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.4
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• pp.274-279
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• 2009

To determine the critical level for optimum maturity of flue-cured tobacco leaves (KF118) at the stalk position from cutter to tips, the reflectance index using ground-based remote sensors and chlorophyll meter were investigated. The sensors estimated were Crop $Circle^{TM}$ (Holland Scientific), Green $Seeker^{TM}$ (Ntech Industries), Spectroradiometer (LICOR, LI-1800), Chlorophyll meter (SPAD502, Minolta), and Field $Scout^{TM}$ Chlorophyll meter (CM-1000, Spectrum). The L, a, b values and greenness for flue-cured leaf were measured and estimated for correlation with sensor's measurement of harvested leaf. On a reflectance curve of 340nm~1100 nm, the reflectance peaks on 550nm and 675 nm for the harvested leaf were lowered as change from light green to darker green. Darker green leaf harvested produced darker flue-cured leaf. The reflectance at 675 nm for flue-cured leaf decreased as greenness increased in the harvested leaf. This result means that the red edge band of 675 nm wavelength is related to the absorbance of chlorophyll for photosynthesis. The greenness of flue-cured leaf showed significantly positive correlation with the entire reflectance indexes for harvested leaf while the L value by colorimeter showed negative correlation with greenness of cured leaf. The critical level for optimum maturity of harvested leaf were less than 22, 135, and 0.43 for SPAD reading, CM-1000 reading, and gNDVI by Crop $Circle^{TM}$, respectively. Consequently, ground-based remote sensing providing a non-destructive real-time assessment of plant greenness could be a useful tool in the selection of optimum maturity of flue-cured tobacco leaves in relation to high quality of flue-cured tobacco.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.55-62
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• 2007

This paper proposes a defective pixel detection algorithm and its hardware structure for CCD/CMOS image sensor. In previous algorithms, the characteristics of image have not been considered. Also, some algorithms need quite a time to detect defective pixels. In order to make up for those disadvantages, the proposed defective pixel detection method detects defective pixels efficiently by considering the edges in the image and verifies them using several frames while checking scene-changes. Whenever scene-change is occurred, potentially defective pixels are checked and confirmed whether it is defective or not. Test results showed that the correct detection rate in a frame was increased 6% and the defective pixel verification time was decreased 60%. The proposed algorithm was implemented with verilog HDL. The edge indicator in color interpolation block was reused. Total logic gate count was 5.4k using 0.25um CMOS standard cell library.