• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Food Engineering Progress
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• v.15 no.2
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• pp.136-142
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• 2011

The objective of this research was to classify intact soybeans and foreign objects using near-infrared (NIR) spectroscopy. Intact soybeans and foreign objects were scanned using a NIR spectrometer equipped with scanning monochromator. NIR spectra of intact soybeans and foreign objects in the wavelength range from 900 to 1800 nm were collected. The classification of intact soybeans and foreign objects were conducted by using partial least-square discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) multivariate methods. Various types of data pretreatments were tested to develop the classification models. Intact soybeans and foreign objects were successfully classified by the PLS-DA prediction model with mean normalization pretreatment. These results showed the potential of NIR spectroscopy combined with multivariate analysis as a method for classifying intact soybeans and foreign objects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.598-603
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• 2019

Three-dimensional shape measurement technology is used in various industries. Among them, optical three-dimensional shape measurement techniques based on the optical trigonometry are mainly used in the field of semiconductor product inspection, where large quantities of three-dimensional shape measurements are made daily in factories and fine measurements are also required. The light source and the drive circuit, which are components of three-dimensional measurement equipment based on this optical trigonometry, produce heat generated by prolonged operation, and may be exposed to conditions where the ambient temperature is not constant, resulting in temperature-induced measurement errors. In this study, the compensation method of the Thermal Errors for Phase Measuring Profilometry is proposed. Three-Dimensional Shape Measurement Equipment based on Phase Measuring Profilometry is implemented to measure the height of an object and ambient temperature for 10 Hours, and a regression line was obtained line by making simple linear regression using measured temperature and height values. This regression line was used to correct the error of the height measurement according to the temperature, and thermal error was from 139.88 um(Micrometer) to 13.12 um.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.24 no.3
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• pp.107-112
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• 2018

The purpose of this study was to investigate the migration levels of lead (Pb), cadmium (Cd) and arsenic (As) from polycarbonate food contact materials into food simulant at different temperatures ($70^{\circ}C$ and $100^{\circ}C$). The method was validated by linearity of calibration curves, limit of detection (LOD), limit of quantification (LOQ), recovery, precision and uncertainty. All of 200 samples, including bottles, cups, containers, ladles, spoons and tongs were purchased from domestic markets and analyzed by inductively coupled plasma mass spectrometry (ICP-MS). Mean concentrations of positive samples were higher at $100^{\circ}C$ than $70^{\circ}C$ as showing a dependency of migration temperature. The migration concentrations ranged from not-detected (ND) to $4.67{\mu}g/L$, ND to $0.49{\mu}g/L$L and ND to $2.91{\mu}g/L$ for Pb, Cd and As, respectively, which were far below the migration limits of Korea standards and specifications for food utensils, containers and packages.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.701-714
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• 2018

The purpose of this study is to show the possibility of 3-dimensional modeling of open-pit limestone mine by using a rotary-wing unmanned aerial vehicle, a drone, and to estimate the amount of mining before and after mining of limestone by explosive blasting. Analysis of the image duplication of the mine has shown that it is possible to achieve high image quality. Analysis of each axis error at the shooting position after analyzing the distortions through camera calibration was shown the allowable range. As a result of estimating the amount of mining before and after explosive blasting, it was possible to estimate the amount of mining of a wide range quickly and accurately in a relatively short time. In conclusion, it is considered that the drone of a rotary-wing unmanned aerial vehicle can be usefully used for the monitoring of open-pit limestone mines and the estimation of the amount of mining. Furthermore, it is expected that this method will be utilized for periodic monitoring of construction sites and road slopes as well as open-pit mines in the future.

• Korean Journal of Plant Resources
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• v.34 no.2
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• pp.177-185
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• 2021

The purpose of this study was to compare the chemical properties of the bokbunja distributed in Korea with the content of the bioactive substance ellagic acid. The bokbunja was Rubus coreanus group and Rubus occidentalis group were compared, domestic bokbunja and import bokbunja were compared. In bokbunja, free sugar was 30.89 ± 0.7 mg/g of Rubus coreanus and 29.05 ± 0.87 mg/g of Rubus occidentalis. and 27.28 ± 7.4 mg/g of domestic bokbunja and 21.58 ± 6.73 mg/g of import bokbunja. The free amino acids was 4.50 ± 0.08 mg/g of Rubus coreanus and 5.05 ± 0.08 mg/g of Rubus occidentalis. and 4.13 ± 1.09 mg/g of domestic bokbunja and 3.75 ± 0.31 mg/g of import bokbunja. Validation of the ellagic acid method was confirmed by comparing the retention time and spectrum of the standard and extract using HPLC. The calibration curve (R²) showed linearity of 0.9999. As a result of analyzing the ellagic acid content of each extraction solvent, DMSO and methanol mixture extracts were high, and Rubus coreanus was 2.56 mg/g and Rubus occidentalis was 3.16 mg/g, which was not significantly different (p < 0.05) In addition, the ellagic acid content of domestic bokbunja and import bokbunja was 2.83 mg/g and 2.99 mg/g, which was not significantly different (p < 0.05).

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1203-1210
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• 2020

Drought is caused by a combination of various hydrological or meteorological factor, so it is difficult to accurately assess drought event, but various drought indices have been developed to interpret them quantitatively. However, the drought indexes currently being used are calculated from the lack of a single variable, which is a problem that does not accurately determine the drought event caused by complex causes. Shortage of a single variable may not be a drought, but it is judged to be a drought. On the other hand, research on developing indices using unstructured data, which is widely used in big data analysis, is being carried out in other fields and proven to be superior. Therefore, in this study, we intend to calculate the drought index by combining unstructured data (news data) with weather and hydrologic information (rainfall and dam inflow) that are being used for the existing drought index, and to evaluate the utilization of drought interpretation through verification of the calculated drought index. The Clayton Copula function was used to calculate the joint drought index, and the parameter estimation was used by the calibration method. The analysis showed that the drought index, which combines unstructured data, properly expresses the drought period compared to the existing drought index (SPI, SDI). In addition, ROC scores were calculated higher than existing drought indices, making them more useful in drought interpretation. The joint drought index calculated in this study is considered highly useful in that it complements the analytical limits of the existing single variable drought index and provides excellent utilization of the drought index using unstructured data.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.4
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• pp.259-264
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• 2020

The aim of this study was to investigate the feasibility of discrimination 12 different cultivar of sorghum × sudangrass hybrid (Sorghum genus) seed through near infrared spectroscopy (NIRS). The amount of samples for develop to the best discriminant equation was 360. Whole samples were applied different three spectra range (visible, NIR and full range) within 680-2500 nm wavelength and the spectrastar 2500 Near near infrared was used to measure spectra. The calibration equation for discriminant analysis was developed partial least square (PLS) regression and discrimination equation (DE) analysis. The PLS discriminant analysis model for three spectra range developed with mathematic pretreatment 1,8,8,1 successfully discriminated 12 different sorghum genus. External validation indicated that all samples were discriminated correctly. The whole discriminant accuracy shown 82 ~ 100 % in NIR full range spectra. The results demonstrated the usefulness of NIRS combined with chemometrics as a rapid method for discrimination of sorghum × sudangrass hybrid cultivar through seed.