• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.543-551
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• 2006

Recently efforts to extract information about forests by using remote sensing techniques for efficient forest management have progressed actively. In terms of extraction of tree information using single remote sensing data, however, the accuracy of tree recognition and the quantity of extracted information is limited. The objective of this study is to carry out tree modeling in domestic environment applying the latest core technique for tree modeling using color aerial photographs and LiDAR data and to estimate the result of tree modeling. A small-scale coniferous forest was investigated in Daejeon. It was 0.77 that the $R^2$ of accuracy test of tree numbers that estimated with color aerial photography and LiDAR data. In terms of tree height, there was no difference between the estimated value and the field measurements in the case of the group accuracy test of the recently unchanged area. Moreover $R^2$ was 0.83 in the case of the individual accuracy test.

• YAKHAK HOEJI
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• v.42 no.1
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• pp.25-30
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• 1998

This study was designed to compare the absorption fraction and extent of ketoprofen gels and a matrix typed ketoprofen plaster patch. 3g (90mg as ketoprofen) of the two gels whi ch has oleohydrogel or hydrogel as a base, respectively, and 3 pieces of plaster patches (90mg as ketoprofen) were, applied in the area of 210$cm^2$ on forearm in 12 volunteers by cross over design. Blood samples were collected serially up to 24 hours and the plasma concentrations of ketoprofen were analyzed by HPLC using flurbiprofen as an internal standard. The detection limit of the assay was 1ng/ml of ketoprofen in plasma. The pharmacokinetic parameters (e.g. $AUC_{24hr}$, $AUMC_{24hr}$, MRT, Fraction Absorbed) were calculated from the plasma concentrations time data of each volunteer. The oleo-hydrogel showed significantly higher absorption fraction and extent of ketoprofen than the current hydrogel. The mean plasma concentrations of the oleo-hydrogel were increased to 98.46${\pm}$23.15ng/ml by 6 hour after application, and increased futher to 100.61${\pm}$18.65ng/ml at 24 hour. On the other hand, those of the hydrogel were increased 17.61${\pm}$18.65ng/ml at 5 hour to 34.68${\pm}$9.65ng/ml at 24 hour gradually. Therefore the plasma concentrations of oleo-hydrogel at each measured time were 3~7 times greater than those of the hydrogel with statistical significance. The $AUC_{24hr}$ (1797.26${\pm}$52.09ng.h/ml) of the oleo-hydrogel was 3.5 times greater (P<0.05) than that (516.17${\pm}$104.52ng.h/ml) of the hydrogel. The plaster patches showed higher bioavailability ($AUC_{24hr}$ 2877.37${\pm}$578.27ng.h/ml) than the olea-hydrogel ($AUC_{24hr}$ 1797.26${\pm}$52.09ng.h/ml) without statistical significance. But the absorption fraction of the oleo-hydrogel was rather higher than that of the plaster patches during the first 6 hours after administration. These results suggest that newly developed ketoprofen gel which is used oleo-hydrogel as a base would show excellent skin permeation on topical application for the corresponding clinical indications and could be absorbed as well as plaster patches.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.683-690
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• 2021

The ventilation system of the engine room of a ship is generally installed to supply the combustion air necessary for the internal combustion engine and to remove the heat source generated in the engine room, and it must satisfy the international standard (ISO 8861) for the design conditions and calculation standards for the ventilation of the ship engine room. The response delay of the ventilation system including the fire detector is affected by the airflow formed inside the area and the location of the fire detector. In this study, to improve the initial fire detection response speed of a fire detector installed on a fishing vessel and to maintain the sensitivity of the installed detector, the smoke behavior was simulated using the air flow field inside the engine room, the amount of combustion air in the internal combustion engine, and the internal pressure of the engine room as variables. Analysis of the simulation results showed that reducing the flow rate in the air flow field and increasing the vortex by reducing the internal pressure of the engine room and installing a smoke curtain would accelerate the rise of the ceiling of the smoke component and improve the smoke detector response speed and ventilation system.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.847-859
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• 2021

Recently, as the number of high-resolution satellite SAR images increases, the demand for precise matching of SAR imagesin change detection and image fusion is consistently increasing. RMSE (Root Mean Square Error) values using GCPs (Ground Control Points) selected by analysts have been widely used for quantitative evaluation of image registration results, while it is difficult to find an approach for automatically measuring the registration accuracy. In this study, a feasibility analysis was conducted on using the FSIM (Feature Similarity) index as a measure to evaluate the registration accuracy. TerraSAR-X (TSX) staring spotlight data collected from various incidence angles and orbit directions were used for the analysis. FSIM was almost independent on the spatial resolution of the SAR image. Using a single SAR image, the FSIM with respect to registration errors was analyzed, then use it to compare with the value estimated from TSX data with different imaging geometry. FSIM index slightly decreased due to the differencesin imaging geometry such as different look angles, different orbit tracks. As the result of analyzing the FSIM value by land cover type, the change in the FSIM index according to the co-registration error was most evident in the urban area. Therefore, the FSIM index calculated in the urban was mostsuitable for determining the accuracy of image registration. It islikely that the FSIM index has sufficient potential to be used as an index for the co-registration accuracy of SAR image.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.493-503
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• 2019

This study presents a new method of estimating the size distribution of river bed gravel through image processing. The analysis was done in two steps; first the individual grain images were analyzed and then the grain particle segmentation of river-bed images were processed. In the first part of the analysis, the relationships (long axes, intermediate axes and projective areas) between grain features from images and those measured were compared. For this analysis, 240 gravel particles were collected at three river stations. All particles were measured with vernier calipers and weighed with scales. The measured data showed that river gravel had shape factors of 0.514~0.585. It was found that the weight of gravel had a stronger correlation with the projective areas than the long or intermediate axes. Using these results, we were able to establish an area-weight formula. In the second step, we calculated the projective areas of the river-bed gravels by detecting their edge lines using the ImageJ program. The projective areas of the gravels were converted to the grain-size distribution using the formula previously established. The proposed method was applied to 3 small- and medium- sized rivers in Korea. Comparisons of the analyzed size distributions with those measured showed that the proposed method could estimate the median diameter within a fair error range. However, the estimated distributions showed a slight deviation from the observed value, which is something that needs improvement in the future.

• Research in Plant Disease
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• v.26 no.4
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• pp.239-249
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• 2020

To find out the cause of the fire blight outbreak in apples and pears of Korea in 2019, we investigated disease appearing situation of thirty fire blight infected orchards, and interviewed farmers to determine the cultivation characteristics. Fire blight occurred mostly in orchards that had infected more than 2 years before. The cause of this were as follows: farmers did not know the symptoms of the disease properly. It is presumed that it has spread from the first occurrence to the surrounding orchards by flower-visiting insects or farmers and to a short distance or a long distance by the same cultivator or co-farmer. These series of processes repeated in the newly spreading area, and then disease reports increased as farmers became aware of fire blight. To minimize the spread of fire blight in Korea, it suggested that thorough education of farmers for early diagnosis and quantitative detection technology that can diagnose even in no symptom showing plants. And chemical or biological spraying systems suitable for domestic cultivation methods, which are producing large fruits, and molecular epidemiological studies of pathogens.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.367-378
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• 2021

Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.69-81
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• 2006

The Computer Forensics is a research area that finds the malicious users by collecting and analyzing the intrusion or infringement evidence of computer crimes such as hacking. Many researches about Computer Forensics have been done so far. But those researches have focussed on how to collect the forensic evidence for both analysis and poofs after receiving the intrusion or infringement reports of hosts from computer users or network administrators. In this paper, we describe how to collect the forensic evidence of good quality from observable and protective hosts at the time of infringement occurrence by malicious users. By correlating the event logs of Intrusion Detection Systems(IDSes) and hosts with the configuration information of hosts periodically, we calculate the value of infringement severity that implies the real infringement possibility of the hosts. Based on this severity value, we selectively collect the evidence for proofs at the time of infringement occurrence. As a result, we show that we can minimize the information damage of the evidence for both analysis and proofs, and reduce the amount of data which are used to analyze the degree of infringement severity.