• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.6
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• pp.95-104
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• 2006

The presence of cavitations under pavements or behind tunnel linings of concrete is likely to result in collapse. One method of detecting such voids by non-destructive means is low frequency type radar(GPR). By the way, the size and thickness of small cavitation can't be detected by the present radar technology with low frequency and low resolution when it apply to civil structures like that. To overcome these problems and limitations, this study aims to develope and propose a new analysis method for estimating the depth, cross-sectional size and thickness of cavitations using low frequency radar. A new proposed method is based on the experiments that are carried out for analyzing the correlation between the measurement values(the amplitudes of radar return) of low frequency radar and various type of cavitations. In this process, the threshold value for radar image processing which aims to represent only cavitations to be fitted size can be obtained. As the results, it is clarified that a proposed method has a possibility of estimating cavitation depth, size and thickness with good accuracy in laboratory scale.

• The Korean Journal of Nuclear Medicine
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• v.30 no.1
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• pp.1-14
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• 1996

Since the publication of the first bone scintiscans in 1962 three decades have elapsed. The bone scan has made great strides during this period, becoming one of the most commonly used nuclear imaging tests. In spite of the progress, however, the specificity of bone scan has remained relatively low. As the result it is a common practice to seek additional information from radiograph, CT scan and MR image, which is euphemistically termed as "image fusion or co-location." The basic reason is the inapplicability of the classical piecemeal analysis to interpreting planar and SPECT bone scans. Such analysis has its base on the observation of elemental features of morphology, which include the size, shape, contour, location, topography and internal architecture. The physiochemical profile may well also be included. Understandably, however, the miniatured images of the planar bone scan cannot provide these features in acceptable detail and the same holds true even with SPECT Images which are but sliced views of the reconstructed planar scans. Fortunately pinhole scanning has the capacity to portray both the morphological and chemical profiles of bone and joint diseases in greater detail through true magnification. The magnitude of pinhole scan resolution is practically comparable to that of radiography as far as gross anatomy is concerned. Thus, we feel strongly that pinhole scanning is a potential breakthrough of the long-lamented low specificity of bone scan. This presentation will discuss the fun-damentals, advantages and disadvantages and the most recent advances of pinhole scanning. It high-lights the actual clinical applications of pinhole scanning in relation to the diagnosis of infective and inflammatory diseases of bone and joint.

• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.379-384
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• 2015

An infrared image sensor is a core device in a thermal imaging system. The fabrication method of a focal plane array (FPA) is a key technology for a high resolution infrared image sensor. Each pixels in the FPA have $Si_3N_4/SiO_2$ membranes including legs to deposit bolometric materials and electrodes on Si readout circuits (ROIC). Instead of polyimide used to form a sacrificial layer, the feasibility of an amorphous silicon (${\alpha}-Si$) was verified experimentally in a $8{\times}8$ micro-bolometer array with a $50{\mu}m$ pitch. The elimination of the polyimide sacrificial layer hardened by a following plasma assisted deposition process is sometimes far from perfect, and thus requires longer plasma ashing times leading to the deformation of the membrane and leg. Since the amorphous Si could be removed in $XeF_2$ gas at room temperature, however, the fabricated micro-bolomertic structure was not damaged seriously. A radio frequency (RF) sputtered nickel oxide film was grown on a $Si_3N_4/SiO_2$ membrane fabricated using a low stress silicon nitride (LSSiN) technology with a LPCVD system. The deformation of the membrane was effectively reduced by a combining the ${\alpha}-Si$ and LSSiN process for a nickel oxide micro-bolometer.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.181-189
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• 2012

Recently, interest in potential for estimating water quality using high resolution satellite images is increasing. However, low SNR(Signal to Noise Ratio) over inland water and radiometric errors such as non-linearity of brightness value of high resolution satellite images often lead to accuracy degradation in water quality estimation. Therefore radiometric correction should be carried out to estimate water quality for high resolution satellite images. For KOMPSAT-2 images parameters for brightness value-radiance conversion are not available and precise radiometric correction is difficult. To exploit KOMPSAT-2 images for water quality monitoring, it is necessary to investigate non-linearity of brightness value and noise over inland water. In this paper, we performed brightness value comparison between KOMPSAT-2 images and IKONOS/GeoEye-1, which are known to show the linearity. We used the images obtained over the same area and on the same date for comparison. As a result, we showed that although KOMPSAT-2 images are more noisy;the trend of brightness value and pattern of noise are almost similar to reference images. The results showed that appropriate target area to minimize the impact of noise was $5{\times}5$. Non-linearity of brightness value between KOMPSAT-2 and reference images was not observed. Therefore we could conclude that KOMPSAT-2 may be used for estimation of water quality parameters such as concentration of chlorophyll.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.957-964
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• 2023

This study focused on hand sanitizer as a medium that can replace ultrasonic gel, which is vulnerable to contamination by bacteria that reside on the hand. Hand sanitizer produces a strong sterilization effect from germs resident on the hands through different sterilization principles depending on the ingredients. Select products of gel type, cream type, and foam type, except for liquid type with low viscosity, and ultrasonically apply one 62% ethanol gel type and one cream type, one benzalkonium chloride 0.066% cream type and one foam type, respectively. Using ATS-539 as a medium, image evaluation was performed on the axial and lateral resolution and penetration depth, and the presence or absence of an air layer between the probe and the phantom. As a result, in the evaluation of the axial and lateral resolution and the depth of penetration, all four experimental groups met the evaluation criteria. However, in the case of the foam type, although it was suitable for the evaluation criteria of resolution and penetration depth, dark shadows appeared on both sides except for the center of observation during image evaluation. Through this experiment, it was possible to confirm the possibility that the remaining three types of hand sanitizers except the foam type could replace the ultrasonic gel.

• Journal of the Korean Society of Radiology
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• v.12 no.2
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• pp.193-199
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• 2018

In this research, 15 patients were diagnosed with 1.5T and 3.0T MRI instruments (Philips, Medical System, Achieva) to minize Ferromagnetic artifact and find the optimized Tesla. Based on the theory that the 3.0T, when compared to 1.5T, show relatively high signal-to-ratio(SNR), Scan time can be shortened or adjust the image resolution. However, when using the 3.0T MRI instruments, various artifact due to the magnetic field difference can degrade the diagnostic information. For the analysis condition, area of interest is set at the background of the T1, T2 sagittal image followed by evaluation of L3, L4, L5 SNR, length of 3 parts with Ferromagnetic artifact, and Histogram. The validity evaluation was performed by using the independent t test. As a result, for the SNR evaluation, mere difference in value was observed for L3 between 1.5T and 3.0T, while big differences were observed for both L4, and L5(p<0.05). Shorter length was observed for the 1.5T when observing 3 parts with Ferromagnetic artifact, thus we can conclude that 3.0T can provide more information on about peripheral tissue diagnostic information(p<0.05). Finally, 1.5T showed higher counts values for the Histogram evaluation(p<0.05). As a result, when we have compared the 1.5T and 3.0T with SNR, length of Ferromagnetic artifact, Histogram, we believe that using a Low Tesla for Spine MRI test can achieve the optimal image information for patients with disk operation like PLIF, etc. in the past.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.296-306
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• 1998

Airborne MSS data is regarded as a potentially effective data source for the measurement of water quality and for the environmental change of water bodies. In this study, we measured the radiance reflectance by using multi-spectral image of low resolution camera(LRC) which will be reached in the multi-purpose satellite(KOMPSAT) to use the data in analyzing water pollution. We also investigated the possibility of extraction of water quality factors in water bodies by using high resolution remote sensing data such as Airborne MSS. Especially, we tried to extract environmental factors related with eutrophication such as chlorophyll-a, suspended sediments and turbidity, and also tried to develop the process technique and the radiance feature of reflectance related with eutrophication. Although it was difficult to explicitly correlate Airborne MSS data with water quality factors due to the insufficient number of ground truth data. The results were summarized as follows: First, the spectrum of sun's rays which reaches the surface of the earth was consistent with visible bands of 0.4${\mu}{\textrm}{m}$~0.7${\mu}{\textrm}{m}$ and about 50% of total quantity of radiation could be found. The spectrum was reached highest at around 0.5${\mu}{\textrm}{m}$ of green spectral band in visible bands. Second, as a result of the radiance reflectance Chlorophyll-a represented high mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and suspended sediments and turbidity represented high at 0.8${\mu}{\textrm}{m}$ and at 0.57${\mu}{\textrm}{m}$, respectively. Finally, as a result of the water quality analysis by using Airborne MSS, Chlorophyll-a could have a distribution image after carrying out ratio of B3 and B5 to B7. Band 7 was useful for making the distribution image of suspended sediments. When we carried out PCA, suspended sediments and turbidity had distributions at PC 1 and PC 4 which are similar to the ground data. Above results can be changed according to the change of season and time. Therefore, in order to analyze the environmental factors of water quality by using LRC data more exactly, we need to investigate the ground data and the radiance feature of reflectance of water bodies constantly. For further studies, we will constantly analyze the radiance feature of the surface of water in wafter bodies by measuring the on-the-spot radiance reflectance and using low resolution satellite image(SeaWiFS). We will also gather the data of water quality analysis in water bodies and analyze the pattern of water pollution.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.