• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1057-1068
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• 2022

This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

• Journal of the Korean earth science society
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• v.41 no.1
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• pp.31-39
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• 2020

Cheonji, the largest caldera lake in Asia, is located at the summit of Baekdu Mountain. Cheonji is covered with snow and ice for about six months of the year due to its high altitude and its surrounding environment. Since most of the sources of water are from groundwater, the water temperature is closely related to the volcanic activity. However, in the 2000s, many volcanic activities have been monitored on the mountain. In this study, we analyzed the dimension of ice produced during winter in Baekdu Mountain using Sentinel-1 satellite image data provided by the European Space Agency (ESA). In order to calculate the dimension of ice from the backscatter image of the Sentinel-1 satellite, 20 Gray-Level Co-occurrence Matrix (GLCM) layers were generated from two polarization images using texture analysis. The method used in calculating the area was utilized with the Support Vector Machine (SVM) algorithm to classify the GLCM layer which is to calculate the dimension of ice in the image. Also, the calculated area was correlated with temperature data obtained from Samjiyeon weather station. This study could be used as a basis for suggesting an alternative to the new method of calculating the area of ice before using a long-term time series analysis on a full scale.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1527-1543
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• 2021

In this paper, we explore the applicability and utility of a technology that generating clustered solid building models based on point cloud automatically by applying it to various data. In order to improve the quality of the model of insufficient quality due to the limitations of the automatic building modeling technology, we develop the building shape modification and texture correction technology and confirmed the resultsthrough experiments. In order to explore the applicability of automatic building model generation technology, we experimented using point cloud and LiDAR (Light Detection and Ranging) data generated based on UAV, and applied building shape modification and texture correction technology to the automatically generated building model. Then, experiments were performed to improve the quality of the model. Through this, the applicability of the point cloud data-based automatic clustered solid building model generation technology and the effectiveness of the model quality improvement technology were confirmed. Compared to the existing building modeling technology, our technology greatly reduces costs such as manpower and time and is expected to have strengths in the management of modeling results.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.213-223
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• 2017

Recently, the air quality of South Korea has deteriorated and public interest has been increasing. Various observation means are used for the monitoring of the atmospheric environment, but it relies on the experience and judgment of the observer in the absence of spatial information on the emission facilities. The purpose of this study was to determine the availability of using drones for monitoring air pollutant emission facilities. A texture transformation method was applied to the drone ortho image to detect the small gas emission facility and the slope data calculated by the digital surface model (DSM) was used to reduce the false alarm ratio. As a result, it shows the possibility of using drones in the detection of small gas emission facilities by showing about 80% of positive detection ratio and 40% of false alarm ratio. In the future, various researches are required to the improve positive detection ratio and the reduction of the false alarm ratio. Based on these results, it is necessary to construct a database including 3D spatial information of air pollutant emission facilities.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.1-8
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• 2019

In this paper, we propose an improved facial skin color extraction method to solve the problem that facial surface is lost due to shadow or illumination in skin color extraction process and skin color extraction is not possible. In the conventional HSV method, when facial surface is brightly illuminated by light, the skin color component is lost in the skin color extraction process, so that a loss area appears on the face surface. In order to solve these problems, we extract the skin color, determine the elements in the H channel value range of the skin color in the HSV color space among the lost skin elements, and combine the coordinates of the lost part with the coordinates of the original image, To minimize the number of In the face detection process, the face was detected using the LBP Cascade Classifier, which represents texture feature information in the extracted skin color image. Experimental results show that the proposed method improves the detection rate and accuracy by 5.8% and 9.6%, respectively, compared with conventional RGB and HSV skin color extraction and face detection using the LBP cascade classifier method.

• Journal of the Korean Society of Radiology
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• v.10 no.6
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• pp.443-450
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• 2016

In this study, we are using a computer tomography image of the abdomen, as an experimental linear research for the image of the fatty liver patients texture features analysis and computer-aided diagnosis system of implementation using the ROC curve analysis, from the computer tomography image. We tried to provide an objective and reliable diagnostic information of fatty liver to the doctor. Experiments are usually a fatty liver, via the wavelet transform of the abdominal computed tomography images are configured with the experimental image section, shows the results of statistical analysis on six parameters indicating a feature value of the texture. As a result, the entropy, average luminance, strain rate is shown a relatively high recognition rate of 90% or more, the control also, flatness, uniformity showed relatively low recognition rate of about 70%. ROC curve analysis of six parameters are all shown to 0.900 (p = 0.0001) or more, showed meaningful results in the recognition of the disease. Also, to determine the cut-off value for the prediction of disease six parameters. These results are applicable from future abdominal computed tomography images as a preliminary diagnostic article of diseases automatic detection and eventual diagnosis.

• Restorative Dentistry and Endodontics
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• v.31 no.2
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• pp.133-139
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• 2006

The purposes of this study were firstly to identify the microbial species on gutta-percha (GP) cones exposed at outpatient clinics using polymerase chain reaction, and secondly to evaluate the rapid sterilization effect of two chemical disinfectants at chair side. It also evaluated the alteration of surface texture of GP cones after 5-min soaking into two chemical disinfectants. A total of 100 GP cones from two endodontic departments were randomly selected for microbial detection using PCR assay with universal primer. After inoculation on the sterilized GP cones with the same microorganism identified by PCR assay, they were soaked in two chemical disinfectants: 5% NaOCl and 2% chlorhexidine for 1, 3, 5, and 10 minutes. The sterilization effect was evaluated by turbidity and subculture. The change of surface textures using a scanning electron microscope was also examined after 5 min-soaking in two chemical disinfectants. Results showed that four bacterial species were detected in 17 GP cones, and all the species belonged to the genus Staphylococcus. Two chemical disinfectants were effective in sterilization with just 1 minute soaking. On the SEM picture of NaOCl-soaked GP cone, a cluster of cuboidal crystals was seen on the cone surface. Present data demonstrate that two chemical disinfectants are useful for rapid sterilization of GP cone just before obturation at chair side, while CHX-soaked GP cone has cleaner surface without crystal precipitation than that of NaOCl-treated cone.

• Journal of radiological science and technology
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• v.35 no.3
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• pp.227-235
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• 2012

Digital Mammography makes it possible to reproduce the entire breast image. And it is used to detect microcalcification and mass which are the most important point of view of nonpalpable early breast cancer, so it has been used as the primary screening test of breast disease. It is reported that microcalcification of breast lesion is important in diagnosis of early breast cancer. In this study, six types of texture features algorithms are used to detect microcalcification on breast US images and the study has analyzed recognition rate of lesion between normal US images and other US images which microcalification is seen. As a result of the experiment, Computer aided diagnosis recognition rate that distinguishes mammography and breast US disease was considerably high 70~98%. The average contrast and entropy parameters were low in ROC analysis, but sensitivity and specificity of four types parameters were over 90%. Therefore it is possible to detect microcalcification on US images. If not only six types of texture features algorithms but also the research of additional parameter algorithm is being continually proceeded and basis of practical use on CAD is being prepared, it can be a important meaning as pre-reading. Also, it is considered very useful things for early diagnosis of breast cancer.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.303-310
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• 2013

Thyroid nodular disease is the most frequently appeared in thyroid disease. Thyroid ultrasonography offers location of nodules, size, the number, information of internal echo characteristic. Thus, it makes possible to sort high-risk nodule containing high possibility about thyroid cancer and to induct precisely when take a Fine Needle Biopsy Aspiration. On thyroid nodule, the case which is diagnosed as malignant is less than 5% but screening test is very important on ultrasound and also must be reduced unnecessary procedure. Therefore, in this study an approach for describing a region is to quantity its texture content. We applied TFA algorithm on case which has been pathologically diagnosed as papillary thyroid cancer. we obtained experiment image which set the ROI on ultrasound and cut the $50{\times}50$ pixel size, histogram equalization. Consequently, Disease recognition detection efficiency of GLavg, SKEW, UN, ENT parameter were high as 91~100%. It is suggestion about possibility on CAD which distinguishes thyroid nodule. In addition, it will be helpful to differential diagnosis of thyroid nodule. If the study on additional parameter algorithm is continuously progressed from now on, it is able to arrange practical base on CAD and it is possible to apply various disease in the thyroid US.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.609-614
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• 2018

This study was conducted to investigate the effects of turmeric powder on jeung-pyun. Turmeric jeung-pyun containing 0%, 0.5%, 1%, 1.5%, and 2% turmeric powder was prepared and the moisture, pH, sugar, color, texture, DPPH and sensory properties of the samples were measured. Moisture contents of jeung-pyun were 51.26~51.99% and there were significant differences among the samples(p<0.001). The L-values were significantly decreased with increasing turmeric powder content. The b-value was low in the control and there were significant differences among the samples(p<0.05). Texture profile analysis showed that there were no significant differences among the groups in hardness, adhesiveness, springiness, cohesiveness, gumminess, and chewiness. The hardness was the lowest in the control group and increased with increasing turmeric powder content. The antioxidant activities as measured by DPPH increased with increasing turmeric powder content (p<0.001). In the sensory evaluation, 1% addition of turmeric powder showed the highest preference in terms of color, taste, flavor, texture and overall preference(p<0.001). As determined by this study, the addition of 1% turmeric powder was the most favorable method for making use of turmeric powder in the production of jueng-pyun.