• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Journal of the Korean Wood Science and Technology
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• v.52 no.3
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• pp.205-220
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• 2024

Various polylactic acid (PLA) blends were reinforced with untreated or silane-treated micro-sized cellulose fiber (MCF), successfully prepared as 3D printing filaments and then printed using a fused filament fabrication (FFF) 3D printer. In this study, we focused on developing 3D-printed MCF/PLA composites through silane treatment of MCF and investigating the effect of silane treatment on the various properties of FFF 3D-printed composites. Fourier transform infrared spectra confirmed the increase in hydrophobic properties of silane-treated MCF by showing the new absorption peaks at 1,100 cm^-1, 1,030 cm^-1, and 815 cm^-1 representing C-NH₂, Si-O-Si, and Si-CH₂ bonds, respectively. In scanning electron microscope images of silane-treated MCF filled PLA composites, the improved interfacial adhesion between MCF and PLA matrix was observed. The mechanical properties of the 3D-printed MCF/PLA composites with silane-treated MCF were improved compared to those of the 3D-printed MCF/PLA composites with untreated MCF. In particular, the highest tensile and flexural modulus values were observed for S-MCF10 (5,784.77 MPa) and S-MCF5 (2,441.67 MPa), respectively. The thermal stability of silane-treated MCF was enhanced by delaying the initial thermal decomposition temperature compared to untreated MCF. The thermal decomposition temperature difference at T₉₅ was around 26℃. This study suggests that the effect of silane treatment on the 3D-printed MCF/PLA composites is effective and promising.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• 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.

• Economic and Environmental Geology
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• v.44 no.6
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• pp.463-474
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• 2011

The Haenam epithermal mineralized zone is located in the southwestern part of South Korea, and hosts low sulfidation epithermal Au-Ag deposit (Eunsan-Moisan) and clay quarries (Okmaesan, Seongsan, and Chunsan). Epithermal deposits and accompanying hydrothermal alteration related to Cretaceous volcanism caused large zoned assemblages of hydrothermal alteration minerals. Advanced argillic-altered rocks with mineral assemblages of alunite-quartz, alunite-dickite-quartz, and dickite-kaolinite-quartz exposed on the Okmaesan, Seongsan, and Chunsan area. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), with three visible and near infrared bands, six shortwave infrared bands, and five thermal infrared bands, was used to identify advanced argillic-altered rocks within the Haenam epithermal mineralized zone. The distinct spectral features of hydrothermal minerals allow discrimination of advanced argillic-altered rocks from non-altered rocks within the study area. Because alunite, dickite, and kaolinite, consisting of advanced argillic-altered rocks within the study area are characterized by Al-O-H-bearing minerals, these acid hydrothermal minerals have a strong absorption feature at $2.20{\mu}m$. The band combination and band ratio transformation cause increasing differences of DN values between advanced argillic-altered rock and non-altered rock. The alunite and dickite-kaolinite of advanced argillic-altered rocks from the Okmaesan, Seongsan, and Chunsan have average DN values of 1.523 and 1.737, respectively. These values are much higher than those (1.211 and 1.308, respectively) of non-altered area. ASTER images can remotely provide the distribution of hydrothermal minerals on the surface. In this way good relation between ASTER spectra analysis and field data suggests that ASTER spectral analysis can be useful tool in the initial steps of mineral exploration.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1607-1622
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• 2022

The purpose of this study is to determine the actual performance of cool roof in preventing absorbed solar radiation. The spatial correlation between surface temperature and absorbed solar radiation is the method by which the performance of a cool roof can be understood and evaluated. The research area of this study is the vicinity of Jangyu Mugye-dong, Gimhae-si, Gyeongsangnam-do, where an actual cool roof is applied. FLIR Vue Pro R thermal infrared sensor, Micasense Red-Edge multi-spectral sensor and DJI H20T visible spectral sensor was used for aerial photography, with attached to the drone DJI Matrice 300 RTK. To perform the spatial correlation analysis, thermal infrared orthomosaics, absorbed solar radiation distribution maps were constructed, and land cover features of roof were extracted based on the drone aerial photographs. The temporal scope of this research ranged over 9 points of time at intervals of about 1 hour and 30 minutes from 7:15 to 19:15 on July 27, 2021. The correlation coefficient values of 0.550 for the normal roof and 0.387 for the cool roof were obtained on a daily average basis. However, at 11:30 and 13:00, when the Solar altitude was high on the date of analysis, the difference in correlation coefficient values between the normal roof and the cool roof was 0.022, 0.024, showing similar correlations. In other time series, the values of the correlation coefficient of the normal roof are about 0.1 higher than that of the cool roof. This study assessed and evaluated the potential of an actual cool roof to prevent solar radiation heating a rooftop through correlation comparison with a normal roof, which serves as a control group, by using high-resolution drone images. The results of this research can be used as reference data when local governments or communities seek to adopt strategies to eliminate the phenomenon of urban heat islands.

• Journal of Dental Rehabilitation and Applied Science
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• v.40 no.2
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• pp.55-63
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• 2024

Purpose: This study aimed to assess the antimicrobial efficacy of an 810-nm infrared diode laser with indocyanine green (ICG) against Staphylococcus aureus on sandblasted, large grit, and acid-etched (SLA) titanium surfaces, comparing its effectiveness with alternative chemical decontamination modalities. Materials and Methods: Biofilms of S. aureus ATCC 25923 were cultured on SLA titanium disks for 48 hours. The biofilms were divided into five treatment groups: control, chlorhexidine gluconate (CHX), tetracycline (TC), ICG, and 810-nm infrared diode laser with ICG (ICG-PDT). After treatment, colony-forming units were quantified to assess surviving bacteria, and viability was confirmed through confocal laser-scanning microscope (CLSM) imaging. Results: All treated groups exhibited a statistically significant reduction in S. aureus (P < 0.05), with notable efficacy in the CHX, TC, and ICG-PDT groups (P < 0.01). While no statistical difference was observed between TC and CHX, the ICG-PDT group demonstrated superior bacterial reduction. CLSM images revealed a higher proportion of dead bacteria stained in red within the ICG-PDT groups. Conclusion: Within the limitations, ICG-PDT effectively reduced S. aureus biofilms on SLA titanium surfaces. Further investigations into alternative decontamination methods and the clinical impact of ICG-PDT on peri-implant diseases are warranted.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.481-491
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• 2014

Blue-ice area is a glacial ice field in ice sheet, ice shelf and glaciers where snow ablation and sublimation is larger than snowfall. As the blue-ice area has large influences on the meteorite concentration mechanism and ice mass balance, it is required to quantify the concentration of blue-ice. We analyzed spectral reflectance characteristics of blue-ice, snow and cloud by using MODIS images obtained over blue-ice areas in McMurdo Dry Valleys, East Antarctica, from 2007 to 2012. We then developed Normalized Difference Blue-ice Index (NDBI) algorithm which quantifies the concentration of blue-ice. Snow and cloud have a high reflectance in visible and near-infrared (NIR) bands. Reflectance of blue-ice is high in blue band, while that lowers in the NIR band. NDBI is calculated by dividing the difference of reflectance in the blue and NIR bands by the sum of reflectances in the two bands so that NDBI = (Blue-NIR)/(Blue + NIR). NDBI calculated from the MODIS images showed that the blue-ice areas have values ranging from 0.2 to 0.5, depending on the exposure and concentration of blue-ice. It is obviously different from that of snow and cloud that has values less than 0.2 or rocks with negative values. The change of NDBI values in the blue-ice area has higher correlation with snow depth ($R^2=0.699$) than wind speed ($R^2=0.012$) or air temperature ($R^2=0.278$), all measured at a meteorological station installed in McMurdo Dry Valleys. As the snow depth increased, the NDBI value decreased, which suggests that snow depth can be estimated from NDBI values over blue-ice areas. The NDBI algorithm developed in this study will be useful for various polar research fields such as meteorite exploration, analysis of ice mass balance as well as the snow depth estimation.

• Journal of the Korean Geographical Society
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• v.40
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• pp.1-13
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• 1989

The brightness temperature from NOAA AVHRR CH 4 images was examined for the metropolitan Seoul area, the capital city of Korea, to detect the characteristics of the urban heat island for this study. Surface data from 21 meteorological stations were compared with the brightness temperatures Through computer enhancement techniques, more than 20 heat islands could be recognized in South Korea, with 1 km spatii resolution at a scale of 1: 200, 00O(Fig. 3, 4 and 6). The result of the analysis of AVHRR CH 4 images over the metropolitan Seoul area can be summerized as follows (1) The pattern of brightness temperature distribution in the metropolitan Seoul area shows a relatively strong temperature contrast between urban and rural areas. There is some indication of the warm brightness temperature zone characterrizing built-up area including CBD, densely populated residential district and industrial zone. The cool brightness temperature is asociaed with the major hills such as Bukhan-san, Nam-san and Kwanak-san or with the major water bodies such as Han-gang, and reservoirs. Although the influence of the river and reservoirs is obvious in the brightness temperauture, that of small-scaled land use features such as parks in the cities is not features such as parks in the cities is not apperent. (2) One can find a linerar relationshop between the brightenss temperature and air temperature for 10 major cities, where the difference between two variables is larger in big cities. Though the coefficient value is 0.82, one can estimate that factors of the heat islands can not be explained only by the size of the cities. The magnitude of the horizontal brightness temperature differences between urban and rural area is found to be greater than that of horizontal air temperature difference in Korea. (3) Also one can find the high heat island intensity in some smaller cities such as Changwon(won(Tu-r=9.0$^{\circ}$C) and Po-hang(Tu-r==7.1$^{\circ}$~)T. he industrial location quotient of Chang-won is the second in the country and Po-hang the third. (4) A comparision of the enhanced thermal infrared imageries in 1986 and 1989, with the map at a scale of 1:200, 000 for the meotropolitan Seoul area showes the extent of possible urbanization changes. In the last three years, the heat islands have been extended in area. zone characterrizing built-up area including (5) Although the overall data base is small, the data in Fig. 3 suggest that brightness tempeautre could ge utilized for the study on the heat island characteristics. Satellite observations are required to study and monitor the impact of urban heat island on the climate and environment on global scale. This type of remote sensing provides a meams of monitoring the growth of urban and suburban aeas and its impact on the environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.