The remotely sensed data, such as satellite imagery and aerial photos, can be used to extract and detect some objects in the image through image interpretation and processing techniques. Significantly, the possibility for utilizing digital map updating and land monitoring has been increased through automatic object detection since spatial resolution of remotely sensed data has improved and technologies about deep learning have been developed. In this paper, we tried to extract plastic greenhouses into aerial orthophotos by using fully convolutional densely connected convolutional network (FC-DenseNet), one of the representative deep learning models for semantic segmentation. Then, a quantitative analysis of extraction results had performed. Using the farm map of the Ministry of Agriculture, Food and Rural Affairsin Korea, training data was generated by labeling plastic greenhouses into Damyang and Miryang areas. And then, FC-DenseNet was trained through a training dataset. To apply the deep learning model in the remotely sensed imagery, instance norm, which can maintain the spectral characteristics of bands, was used as normalization. In addition, optimal weights for each band were determined by adding attention modules in the deep learning model. In the experiments, it was found that a deep learning model can extract plastic greenhouses. These results can be applied to digital map updating of Farm-map and landcover maps.
Journal of the Korea Society of Computer and Information
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v.28
no.4
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pp.105-112
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2023
In this paper, we propose a new method for displaying colored defects by measuring the relative density with the wide-area and local densities of X-ray. The relative density of one pixel represents a relative difference from the surrounding pixels, and we also suggest a colorization of X-ray images representing these pixels as normal and defective. The traditional method mainly inspects materials such as plastics and metals, which have large differences in transmittance to the object. Our proposed method can be used to detect defects such as sprouts or holes in images obtained by an inspection machine that detects X-rays. In the experiment, the products that could not be seen with the naked eye were colored with pests or sprouts in a specific color so that they could be used in the agricultural product selection system. Products that are uniformly filled with a single ingredient inside, such as potatoes, carrots, and apples, can be detected effectively. However, it does not work well with bumpy products, such as peppers and paprika. The advantage of this method is that, unlike machine learning, it doesn't require large amounts of data. The proposed method could be applied to a screening system using X-rays and used not only in agricultural product screening systems but also in manufacturing processes such as processed food and parts manufacturing, so that it can be actively used to select defective products.
Background: A nondestructive test is commonly used to inspect the surface defects and internal structure of an object without any physical damage. X-rays generated from an electron accelerator or a tube are one of the methods used for nondestructive testing. The high penetration of X-rays through materials with low atomic numbers makes it difficult to discriminate between these materials using X-ray imaging. The interaction characteristics of neutrons with materials can supplement the limitations of X-ray imaging in material discrimination. Materials and Methods: The radiation image acquisition process for air-cargo security inspection equipment using X-rays and neutrons was simulated using a GEometry ANd Tracking (Geant4) simulation toolkit. Radiation images of phantoms composed of 13 materials were obtained, and the R-value, representing the attenuation ratio of neutrons and gamma rays in a material, was calculated from these images. Results and Discussion: The R-values were calculated from the simulated X-ray and neutron images for each phantom and compared with those obtained in the experiments. The R-values obtained from the experiments were higher than those obtained from the simulations. The difference can be due to the following two causes. The first reason is that there are various facilities or equipment in the experimental environment that scatter neutrons, unlike the simulation. The other is the difference in the neutron signal processing. In the simulation, the neutron signal is the sum of the number of neutrons entering the detector. However, in the experiment, the neutron signal was obtained by superimposing the intensities of the neutron signals. Neutron detectors also detect gamma rays, and the neutron signal cannot be clearly distinguished in the process of separating the two types of radiation. Despite these differences, the two results showed similar trends and the viability of using simulation-based radiation images, particularly in the field of security screening. With further research, the simulation-based radiation images can replace ones from experiments and be used in the related fields. Conclusion: The Korea Atomic Energy Research Institute has developed air-cargo security inspection equipment using neutrons and X-rays. Using this equipment, radiation images and R-values for various materials were obtained. The equipment was reconstructed, and the R-values were obtained for 13 materials using the Geant4 simulation toolkit. The R-values calculated by experiment and simulation show similar trends. Therefore, we confirmed the feasibility of using the simulation-based radiation image.
Yeeun Kang;Soyoung Ham;Seungchae Joa;Hani Lee;Seongmin Kim;Hakkyong Kim
Convergence Security Journal
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v.24
no.1
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pp.59-68
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2024
With advancements in artificial intelligence technology, intelligent CCTV systems are being deployed across various environments, such as river bridges and construction sites. However, a conflict arises regarding the opening and closing of rooftop access points due to concerns over potential accidents and crime incidents and their role as emergency evacuation spaces. While the relevant law typically mandates the constant opening of designated rooftop access points, closures are often tacitly permitted in practice for security reasons, with a lack of appropriate legal measures. In this context, this study proposes a detection system utilizing intelligent CCTV to respond to emergencies that may occur on rooftops. We develop a system based on the YOLOv5 object detection model to detect assault and suicide attempts by jumping, introducing a new metric to assess them. Experimental results demonstrate that the proposed system rapidly detects assault and suicide attempts with high accuracy. Additionally, through a legal analysis of rooftop access point management, deficiencies in the legal framework regarding rooftop access and CCTV installation are identified, and improvement measures are proposed. With technological and legal improvements, we believe that crime and accident incidents in rooftop environments will decrease.
Journal of the Korean Association of Geographic Information Studies
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v.9
no.1
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pp.158-167
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2006
The object of this study is to detect of land-cover change in western DMZ and vicinity. This was performed as a basic study to construct a decision support system for the conservation or a sustainable development of the DMZ and Vicinity near future. DMZ is an is 4km wide and 250km long and it's one of the most highly fortified boundaries in the world and also a unique thin green line. Environmentalists want to declare the DMZ as a natural reserve and a biodiversity zone, but nowadays through the strengthening of the inter-Korean economic cooperation, some developers are trying to construct a new-town or an industrial complex inside of the DMZ. This study investigates the current environmental conditions, especially deforestation of the western DMZ adopting remote sensing and GIS techniques. The Land-covers were identified through the linear spectvral mixture analysis(LSMA) which was used to handle the spectral mixture problem of low spatial resolution imagery of Landsat TM and ETM+ imagery. To analyze quantitative and spatial change of vegetation-cover in western DMZ, GIS overlay method was used. In LSMA, to develop high-quality fraction images, three endmembers of green vegetation(GV), soil, water were driven from pure features in the imagery. Through 15 years, from 1987 to 2002, forest of western DMZ and vicinity was devastated and changed to urban, farmland or barren land. Northern part of western DMZ and vicinity was more deforested than that of southern part. ($52.37km^2$ of North Korean forest and $39.04km^2$ of South Korean were change to other land-covers.) In case of North Korean part, forest changed to barren land and farmland and in South Korean part, forest changed to farmland and urban area. Especially, In North Korean part of DMZ and vicinity, $56.15km^2$ of farmland changed to barren land through 15 years, which showed the failure of the 'Darakbat' (terrace filed) project which is one of food increase projects in North Korea.
Chun, Jin-Kyong;Kim, Chang Ki;Kim, Hyun Sook;Jung, Ghee Young;Linton, John A.;Kim, Ki Hwan;Lee, Taek Jin;Jeon, Ji Hyun;Kim, Dong Soo
Clinical and Experimental Pediatrics
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v.51
no.9
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pp.971-976
/
2008
Purpose : Surveillance for detecting and managing latent tuberculosis infection (LTBI) is a key component of tuberculosis control. The classic surveillance tool, the tuberculin skin test (TST), may have some limitations when used in the Bacillus Calmette-$Gu{\acute{e}}rin$ (BCG)-vaccinated population. The object was to perform a blood test $QuantiFERON^{(R)}$-TB Gold In Tube (QFT-G IT) based on the detection of interferon-$\gamma$ ($IFN-{\gamma}$) released by T cells in response to Mycobacterium tuberculosis-specific antigens, and to compare the efficacy of this new diagnostic tool for LTBI with that of TST. Methods : For six months, between October 1, 2006 and April 30, 2007, data were collected from 111 patients under 15 years of age at Severance Children's Hospital. TST and QFT-G IT tests were performed with children with or without contact histories of tuberculosis. In addition to these tests, we examined comparative data from 29 adults who had tuberculosis, to detect false negative rates in the QFT-G IT method. Results : Thirty-three children had household contact histories. In this group, 15% and 42% of cases were found to be positive using the QFT-G IT assay and TST, respectively. Agreement was low between these two tests (${\kappa}=0.39$). In the adult active tuberculosis group, the QFT-G IT false negative rate defined as a positive culture and a negative QFT-G IT result was 12.5%. Conclusion : In diagnosing LTBI in children, the usefulness of a whole-blood $IFN-{\gamma}$ assay employing TB-specific antigens will be revealed only by examining additional longitudinal clinical data; this study serves as a starting point in that process.
Purpose : To evaluate the diagnostic significance of simultaneous examination of hematuria and proteinuria in the urinary mass screening for early detection ot incipient renal diseases. Method and Object : During the period of 4 months from August to December in 1997, we did urinary mass screening on students of first grade of high school (16 years aged group) nationwide together with Korean Association of Health(KAH). In the first screening test, Comber-10 $N^{(R)}$ M dipsticks were used to detect proteinuria, hematuria, pyuria and nitrite simultaneously. Total 26,508 students (16 years aged group) from 33 high schools in every province in Korea, respectively, complied to the urinary mass screening. After then, one high school in Seoul was selected to reveal the true incidence of incipient renal diseases among students who showed hematuria in the initial screening through intensive examinations. Those who had hematuria and/or proteinuria visited the Paik hospital, and underwent blood tests and ultrasonographic examinations. The results were evaluated. Results 1) The initial screening revealed that the prevalence of proteinuria, hematuria, pyuria and positive nitrite urine, were $0.73\%,\;2.69\%,\;0.23\%\;and\;0.03\%$, respectively. 2) The first urinary screening among 875 students from one high school in Seoul selected fir the second test showed proteinuria, hematuria, pyuria and positive nitrite urine, were $0.91\%,\;4.68\%,\;0.34\%\;and\;0\%$, respectively. a) Total 8 among 875 students showed proteinuria, but one of them had orthostatic proteinuria and those remaining 7 students had transient proteinuria. b) There were 41 students who had hematuria in the initial screening. Among 33 who complied the second test, only one student showed asymptomatic isolated hematuria and those remaining students were normal. Conclusion : 1) Because of high false positive hematuria rate in the urinary mass screening, it dosen't seem to be appropriate that hematuria screening using dipsticks be included in the urinary mass screening. 2) A unified organization is needed from the fret that so various results of urinary mass screening came out. 3) Positive rates of pyuria and nitrite were so low that validity of urinary mass screening for urinary tract infection needs more studies.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.38
no.4
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pp.363-373
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2020
During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.
According to the Annex 17 to the Convention on International Civil Aviation, an appropriate authority of each contracting state has to define and allocate tasks and coordinate activities between the departments, agencies and other organizations of the State, airport and aircraft operators and other entities concerned with or responsible for the implementation of various aspects of the national civil aviation security programme. The airport has to take leading role in implementing security tasks at airport area because the airport operator is the provider of airport facilities and services to its customer and the security activities belong to its services. So Republic of Korea Government enact the Law, Aviation Safety and Security. The Purpose of this Act is to prevent any unlawful act in airport facilities with international conventions, including the ICAO to provide for standards, procedures and mandatory matters needed to ensure the safety and security of civil aviation. But the Act has some error. So is this paper to review the revision of aviation security regulation and the changes of aviation security responsibilities and task assignment. There is the term "aviation security personnel", who are charged with the task of preventing any act of disrupting the order and safety in airport. But there is no term "security screening personnel" who performs to detect or search for dangerous object, such as weapons or explosives, which may be used for the unlawful obstruction.
Song, Ji-Yong;Jeong, Jong-Chul;Lee, Peter Sang-Hoon
Korean Journal of Environment and Ecology
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v.32
no.6
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pp.686-697
/
2018
Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.
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