• Journal of the Korean earth science society
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• v.26 no.7
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• pp.683-690
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• 2005

As remote sensing imagery with high spatial resolution (e.g. pixel resolution of 1m or less) is used widely in the specific application domains, the requirements of advanced methods for this imagery are increasing. Among many applicable methods, the texture image analysis, which was characterized by the spatial distribution of the gray levels in a neighborhood, can be regarded as one useful method. In the texture image, we compared and analyzed different results according to various directions, kernel sizes, and parameter types for the GLCM algorithm. Then, we studied spatial feature characteristics within each result image. In addition, a template matching program which can search spatial patterns using template images selected from original and texture images was also embodied and applied. Probabilities were examined on the basis of the results. These results would anticipate effective applications for detecting and analyzing specific shaped geological or other complex features using high spatial resolution imagery.

• Journal of the Korean Society of Radiology
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• v.1 no.1
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• pp.11-16
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• 2007

In this study, we have performed contrast-detail analysis for an amorphous selenium(a-Se) based digital X-ray imaging system by using a contrast-detail phantom(CDRAD 2.0) to test its low contrast performance. The X-ray imaging system utilizes an 500-mm-thick a-Se semiconductor X-ray absorber coated over an amorphous silicon(a-Si) TFT(thin-film transistor) detector matrix with a $139mm{\times}139mm$ pixel size and a $46.7cm{\times}46.7cm$ active area. In the measurement of contrast-detail curves we first acquired X-ray images of the CDRAD 2.0 phantom at given test conditions(i.e., 40, 50, 60, 70, 80 kVp, and 16 mA.s), and then evaluated the contrast-detail characteristics of the imaging system from each phantom image by using an image quality factor called the image-quality-figure-inverse(IQFinv). The IQFinv values for the imaging system gradually improved with the photon fluence, indicating the improvement of image visibility: 24.4, 35.3, 39.2, 41.5, and 43.4 at photon fluences of $1.8{\times}105$, $5.9{\times}105$, $11.3{\times}105$, $19.4{\times}105$, and $29.4{\times}105$ photons/$mm^2$, respectively.

• Spatial Information Research
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• v.22 no.3
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• pp.47-58
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• 2014

The credible measurement, reporting and verification (MRV) is among the most critical elements in UN-REDD (United Nations programme on Reducing Emissions from Deforestation and forest Degradation in Developing Countries). This study is intended to explore MRV potential in terms of UN-REDD opportunity cost estimation using satellite image for Mt. Geum-gang of North Korea. A visual interpretation were conducted to evaluate MRV conditions by sub-dividing or decomposing the images with different pixel size into a three types of hierarchical tree structure that helps dealing with spatial variability within each subarea. The permanent record of standard satellite remote sensing system demonstrated its capability of presenting area-wide visual evidences of MRV conditions in Mt. Geum-gang (such as the identification of forested area, degradation trends for forest space, three types of hierarchical land-cover and land use tree structure, carbon density in the landscape). Satellite data could be accepted as legally binding proof when it comes to REDD opportunity cost estimation since several cases exist where remote sensing has been used as legal evidence in ICJ (International Court of Justice) and UN resolution. It doesn't seem very difficult to comply with MRV requirements for UN-REDD opportunity cost calculation due to the probative value of satellite data. It is anticipated that this research output could be used as a valuable reference for Korea-based enterprises exploring REDD project sites and the carbon traders to ensure MRV potentials using satellite image in UN-REDD Opportunity Cost estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.470-477
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• 2013

The aim of this study is to suggest a detection method of water surface location and its evaluation results of application for same vertical position in two successive images with time interval including both staff gauge and water surface. A specific rectangular inspection area is defined from the top of watermark and then the correlation coefficients for the inspection area of the same position of two images with short time interval is calculated. Accordingly, it is possible to identify differences between changing area and fixed area of pixel density by the water flow. The photographs taken in the laboratory were analyzed in order to validate the proposed technique. As the result of the experiment, it is identified that characteristic of correlation coefficients depends on the size of the inspection area. In the case that the inspection area is within the entire width of the watermark, water surface characteristic according to correlation coefficients is clearly noticeable. Thus, it is identified that the proposed technique can be utilized to search water surfaces. Besides, using corelation analysis of two images with time interval, it is identified that error range between 10 and 42cm was reduced in the level of 2.6cm or less in the contaminated photo of existing image stage gauge. Therefore, it is expected that the suggested method can be utilized to enhance image stage gauge performance improving the previous water surface detection method.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.121-133
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• 2005

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of the useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program based on GLCM algorithm is newly implemented. As well, texture imaging modules for GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV Texture imaging parameters, it composed of six types of second order texture functions such as Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality in GLCM/GLDV, two direction modes such as Omni-mode and Circular mode newly implemented in this program are provided with basic eight-direction mode. Omni-mode is to compute all direction to avoid directionality complexity in the practical level, and circular direction is to compute texture parameters by circular direction surrounding a target pixel in a kernel. At the second phase of this study, some case studies with artificial image and actual satellite imagery are carried out to analyze texture images in different parameters and modes by correlation matrix analysis. It is concluded that selection of texture parameters and modes is the critical issues in an application based on texture image fusion.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.623-627
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• 2021

Cervical foraminal stenosis is a disease in which the nerves that pass from the spinal canal to the limbs are narrowed and the nerves are compressed or damaged. Due to the lack of an imaging method that provides quantitatively stenosis, this study attempted to evaluate the area of the cervical vertebrae by reconstructing a three-dimensional computed tomography image, and to determine the area of the neural foramen in normal adults to calculate the stenosis rate. Using a three-dimensional image processing program, the surrounding bones including the posterior spinous process, lateral process, and lamellar bones of the cervical vertebra were removed so that the neural foramen could be observed well. A region of interest including the neural foraminal area of the three-dimensional image was set using ImageJ, and the number of pixels in the neural foraminal area was measured. The neural foraminal area was calculated by multiplying the number of measured pixels by the pixel size. To measure the largest neural foraminal area, it was measured between 40~50 degrees in the opposite direction and 15~20 degrees toward the head. The average area of the right C2-3 foramen was 44.32 mm², C3-4 area was 34.69 mm², C4-5 area was 36.41 mm², C5-6 area was 35.22 mm², C6-7 area was 36.03 mm². The average area of the left C2-3 foramen was 42.71 mm², C3-4 area was 32.23 mm², C5-6 area was 34.56 mm², and C6-7 area was 31.89 mm². By creating a reference table based on the neural foramen area of normal adults, the stenosis rate of patients with neural foraminal stenosis could be quantitatively calculated. It is expected that this method can be used as basic data for the diagnosis of cervical vertebral foraminal stenosis.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.67-67
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• 2003

It is crucial to minimize setup errors of a cancer treatment machine using a high energy and to perform precise radiation therapy. Usually, port film has been used for verifying errors. The Korea Cancer Center Hospital (KCCH) has manufactured digital electronic portal imaging device (EPID) system to verify treatment machine errors as a Quality Assurance (Q.A) tool. This EPID was consisted of a metal/fluorescent screen, 45$^{\circ}$ mirror, a camera and an image grabber and could display the portal image with near real time KIRAMS has also made the acrylic phantom that has lead line of 1mm width for ligh/radiation field congruence verification and reference points phantom for using as an isocenter on portal image. We acquired portal images of 10$\times$10cm field size with this phantom by EPID and portal film rotating treatment head by 0.3$^{\circ}$, 0.6$^{\circ}$ and 0.9$^{\circ}$. To check field size, we acquired portal images with 18$\times$18cm, 19$\times$19cm and 20$\times$20cm field size with collimator angle 0$^{\circ}$ and 0.5$^{\circ}$ individually. We have performed Flatness comparison by displaying the line intensity from EPID and film images. The 0.6$^{\circ}$ shift of collimator angle was easily observed by edge detection of irradiated field size on EPID image. To the extent of one pixel (0.76mm) difference could be detected. We also have measured field size by finding optimal threshold value, finding isocenter, finding field edge and gauging distance between isocenter and edge. This EPID system could be used as a Q.A tool for checking field size, light/radiation congruence and flatness with a developed video based EPID.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.679-684
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• 2023

Venous puncture is widely used to obtain blood samples for pathological examination. Because the invasive venipuncture method using a needle is repeatedly performed, the pain suffered by the patient increases, so our research team pre-developed a miniaturized near-infrared (NIR) imaging system in advance. To improve the image quality of the acquired NIR images, this study aims to model the non-local means (NLM) algorithm, which is well known to be efficient in noise reduction, and analyze its applicability in the system. The developed NIR imaging system is based on the principle that infrared rays pass through dichroic and long-pass filters and are detected by a CMOS sensor module. The proposed NLM algorithm is modeled based on the principle of replacing the pixel from which noise is to be removed with a value that reflects the distances between surrounding pixels. After acquiring an NIR image with a central wavelength of 850 nm, the NLM algorithm was applied to segment the final vein area through histogram equalization. As a result, the coefficient of variation of the NIR image of the vein using the NLM algorithm was 0.247 on average, which was an excellent result compared to conventional filtering methods. In addition, the dice similarity coefficient value of the NLM algorithm was improved by 62.91 and 9.40%, respectively, compared to the median filter and total variation methods. In conclusion, we demonstrated that the NLM algorithm can acquire accurate segmentation of veins acquired with a NIR imaging system.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• Progress in Medical Physics
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• v.20 no.2
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• pp.72-79
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• 2009

Scatter correction for I-131 plays a very important role to improve image quality and quantitation. I-131 has multiple and higher energy gamma-ray emissions. Image quality and quantitative accuracy in I-131 imaging are degraded by object scatter as well as scatter and septal penetration in the collimator. The purpose of this study was to estimate scatter and septal penetration and investigate two scatter correction methods using Monte Carlo simulation. The gamma camera system simulated in this study was a FORTE system (Phillips, Nederland) with high energy, general-purpose, parallel hole collimator. We simulated for two types of high energy collimators. One is composed of lead, and the other is composed of artificially high Z number and high density. We simulated energy spectrum using a point source in air. We estimated both full width at half maximum (FWHM) and full width at tenth maximum (FWTM) using line spread function (LSF) in cylindrical water phantom. We applied two scatter correction methods, triple energy window scatter correction (TEW) and extended triple energy window scatter correction (ETEW). The TEW method is a pixel-by pixel based correction which is easy to implement clinically. The ETEW is a modification of the TEW which corrects for scatter by using abutted scatter rejection window, which can overestimate or the underestimate scatter. The both FWHM and FWTM were estimated as 41.2 mm and 206.5 mm for lead collimator, respectively. The FWHM and FWTM were estimated as 27.3 mm and 45.6 mm for artificially high Z and high density collimator, respectively. ETEW showed that the estimation of scatter components was close to the true scatter components. In conclusion, correction for septal penetration and scatter is important to improve image quality and quantitative accuracy in I-131 imaging. The ETEW method in scatter correction appeared to be useful in I-131 imaging.