• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.37-44
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• 2019

This study was conducted to identify the distribution characteristics of small village wetlands in Geumsan County, an inland mountain zone, and comparing with Seocheon County, a coastal plain area with different ecological environment characteristics. Using Arc-GIS (v10.1) the village wetland code was extracted to derive the possible location of the village wetland, and the final distribution of the village was obtained by performing indoor judging work based on satellite images, aerial photographs, topographical maps, Korea Land Information System (KLIS), land use level, land cover degree (division), and land use status by local surveying and indoor analyzing. Although Geumsan County (576.66km2) is more than 60% larger than Seocheon County (358.04km2), 607 villages in Geumsan County and 570 villages in Seocheon County are capable of making similar levels of 106.5% of wetlands, but only a fraction of those in Seocheon County were found to be 67.6%. The density of the village wetlands was much lower than that of Seocheon County, a coastal plain area, because there were many mountainous areas in Geumsan County, and most of the wetlands temporarily created for water supply were removed during the analysis phase of the Jeongsa Image, so the actual wetlands of the village were judged to be only two-thirds different from those of Seocheon County.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.160-173
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• 2013

In this paper, we propose a new visual odometry technique by combining a forward-looking stereo camera and a backward-looking monocular camera. The main goal of the proposed technique is to identify the location of a moving vehicle which travels long distance and comes back to the initial position in urban road environments. While the vehicle is moving to the destination, a global 3D map is updated continuously by a stereo visual odometry technique using a graph theorem. Once the vehicle reaches the destination and begins to come back to the initial position, a map-based monocular visual odometry technqieu is used. To estimate the position of the returning vehicle accurately, 2D features in the backward-looking camera image and the global map are matched. In addition, we utilize the previous matching nodes to limit the search ranges of the next vehicle position in the global map. Through two navigation paths, we analyze the accuracy of the proposed method.

• Journal of the Korean earth science society
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• v.27 no.6
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• pp.643-652
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• 2006

Data of the carbon monoxide concentration observed in Mt. Waliguan in China (WLG), Ulaan Uul in Mongolia (UUM), Tae-ahn Peninsula in Korea (TAP), and Ryori in Japan (RYO) were analyzed for a long period between 1991 and 2004. The annual average concentration of carbon monoxide was the highest at TAP $(233{\pm}41ppb)$ followed by $RYO(171{\pm}36ppb),\;UUM(155{\pm}26ppb),\;and\;WLG(135{\pm}22ppb)$. The seasonal variations being high in spring and low in summer were observed in other areas of Eastern Asia except WLG. TAP was high in carbon monoxide concentration in all seasons compared to WLG, UUM and RYO and shows wide distribution of concentration in the histogram, which is caused by the influence of large-scale air pollution due to its downwind location close to the East Asian continent, China in particular. Also, our data was compared with data measured at Mauna Loa (MLO) in Hawaii. According to the origin of the isentropic backward trajectory and its transport passage, carbon monoxide concentration observed in TAP was analyzed as follows: continental background airflows (CBG) were $216{\pm}47ppb$; regionally polluted continental airflows (RPC) were $316{\pm}56ppb$; Oceanic background airflows (OBG) were $108{\pm}41ppb$; and Partly perturbed oceanic airflows (PPO) were $161{\pm}6ppb$. The high concentration of carbon monoxide in TAP is due to the airflow from East Asian continent origin rather than that from the North Pacific origin. Especially, RPC which passes through the eastern China appeared to be the highest in concentration in spring, fall, and winter. However, OBG was affected by the North Pacific air mass with a low carbon monoxide concentration in summer. The NOAA satellite images and GEOS-CHEM model simulation confirmed a large-scale air pollution event that was in the course of expansion from southeastern China bound to the Korean Peninsula and the Korea East Sea by way of the Yellow Sea.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.93-102
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• 1996

For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.

• Journal of the Korean Society of Radiology
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• v.10 no.5
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• pp.299-305
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• 2016

Despite of the development of medical equipments and technology. Pancreatic cancer has maked high false positive rate and low survival rate compared to other cancers. Therefore, early catch of pancreatic cancer is the only way to enhance the viability. It is important to find the exact location of the pancreas cancer in early stage. The method of optimum scan for early detection of pancreatic cancer on PET/CT exam is proposed. Examined the anatomical region that potentially can be missing from the supine position of ordinary pet/ct exam. The characteristics and usefulness of angle variation ($0^{\circ}$, $30^{\circ}$, $45^{\circ}$, $60^{\circ}$, $90^{\circ}$) of patients scan position is analyzed. The proposed scan method (named JJ-projection) is bringing advantage of anatomical discrimination by separating stomach, liver, gallbladder duodenum and pancreas. ROC curve analysis is shows to advantage of the JJ-Projection method. The sensitivity has increased 4.6% than the supine delay scan method, the results sensitivity has increased from 91% to 95.2%. The specificity has increased from 75.1% to 84%. Compared with the results observed in cancer by biological biopsy, The accuracy has increased from 86.8% to 94.1%.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.86-92
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• 2002

The feasibility of counting number of small vessels and position in Korean waters using the panchromatic imageries derived from the IRS-1C was tested. The parameters for interpretation of satellite's imageries of small vessels were location(position), size, shape, shadow, tone, texture and pattern, height and depth, situation and association with other vessels. The position of small vessels in the sea without GCP(ground control point) was considered to be inclusive in the satellite imagery with 35 km semi-diameter, denoting rough geographical position of the vessel. The size of vessel was measured by length from stem to stern of the vessel, distinguished by following wave on the surface water. Offshore fishing vessels were separated from merchant ships by their length smaller than 100 m. The shape of vessels on panchromatic imagery of IRS-1C appeared just streamline. In case of clouds which were similar to the shape of small vessels, we were able to distinguish between vessel and cloud by shadow of cloud in the water surface. The tone of sea surface was dark black while small vessel appeared bright white. Small vessel was distinguished from the rough texture of the sea surface and the regular pattern of the waves with white capes when weather was not so good. The situation of the fishing activity was estimated by information of fishing method related to the fishing boat such as the pair trawl in the Yellow Sea.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.132-139
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• 2015

Visual SLAM(Simultaneous Localization And Mapping) has been used widely to estimate a mobile robot's location. Visual SLAM estimates relative motions with static visual features over image sequence. Because visual SLAM methods assume generally static features in the environment, we cannot obtain precise results in dynamic situation including many moving objects: cars and human beings. This paper presents a stereo vision based SLAM method in dynamic environment. First, we extract disparity map with stereo vision and compute optical flow. We then compute disparity change that is the estimated flow field between stereo views. After examining the disparity change value, we detect ROIs(Region Of Interest) in disparity space to determine dynamic scene objects. In indoor environment, many structural planes like walls may be determined as false dynamic elements. To solve this problem, we segment the scene into planar structure. More specifically, disparity values by the stereo vision are projected to X-Z plane and we employ Hough transform to determine planes. In final step, we remove ROIs nearby the walls and discriminate static scene elements in indoor environment. The experimental results show that the proposed method can obtain stable performance in dynamic environment.

• Progress in Medical Physics
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• v.27 no.4
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• pp.250-257
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• 2016

The purpose of this study was to compare the patient setup errors of two different immobilization devices (Feet Fix: FF and Leg Fix: LF) for pelvic region radiotherapy in Tomotherapy. Thirty six-patients previously treated with IMRT technique were selected, and divided into two groups based on applied immobilization devices (FF versus LF). We performed a retrospective clinical analysis including the mean, systematic, random variation, 3D-error, and calculated the planning target volume (PTV) margin. In addition, a rotational error (angles, $^{\circ}$) for each patient was analyzed using the automatic image registration. The 3D-errors for the FF and the LF groups were 3.70 mm and 4.26 mm, respectively; the LF group value was 15.1% higher than in the FF group. The treatment margin in the ML, SI, and AP directions were 5.23 mm (6.08 mm), 4.64 mm (6.29 mm), 5.83 mm (8.69 mm) in the FF group (and the LF group), respectively, that the FF group was lower than in the LF group. The percentage in treatment fractions for the FF group (ant the LF group) in greater than 5 mm at ML, SI, and AP direction was 1.7% (3.6%), 3.3% (10.7%), and 5.0% (16.1%), respectively. Two different immobilization devices were affected the patient setup errors due to different fixed location in low extremity. The radiotherapy for the pelvic region by Tomotherapy should be considering variation for the rotational angles including Yaw and Pitch direction that incorrect setup error during the treatment. In addition the choice of an appropriate immobilization device is important because an unalterable rotation angle affects the setup error.