• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.44 no.3
• /
• pp.218-227
• /
• 2016

Korean government plans to launch a lunar orbiter and a lander to the Moon by 2020. Before launch these two proves, an experimental lunar orbiter will be launched by 2018 to obtain key space technologies for the lunar exploration. Several payloads equipped in experimental lunar orbiter will monitor the surface of the Moon and will gather science data. Lunar orbiter sends telemetry and receives tele-command from ground using S-band while science data is sent to ground stations using X-band when the visibility is available. Korean deep space network will be mainly used for S and X-band communication with lunar orbiter. Deep Space Network or Universal Space Network can also be used for the S-band during trans-lunar phase when korean deep space network is not available and will be used for the S-band in normal mission orbit as a backup. This paper analyzes a visibility condition based on the combination of various ground antennas and its mask angles according to mission scenario to predict the number of contacts per day and to build an operational scenario for the lunar orbiter.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.4
• /
• pp.256-262
• /
• 2004

A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.153-163
• /
• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• Journal of IKEEE
• /
• v.9 no.1 s.16
• /
• pp.7-18
• /
• 2005

A key component of an autonomous mobile robot is to localize itself accurately and build a map of the environment simultaneously. In this paper, we propose a vision-based mobile robot localization and mapping algorithm using scale-invariant features. A camera with fisheye lens facing toward to ceiling is attached to the robot to acquire high-level features with scale invariance. These features are used in map building and localization process. As pre-processing, input images from fisheye lens are calibrated to remove radial distortion then labeling and convex hull techniques are used to segment ceiling region from wall region. At initial map building process, features are calculated for segmented regions and stored in map database. Features are continuously calculated from sequential input images and matched against existing map until map building process is finished. If features are not matched, they are added to the existing map. Localization is done simultaneously with feature matching at map building process. Localization. is performed when features are matched with existing map and map building database is updated at same time. The proposed method can perform a map building in 2 minutes on $50m^2$ area. The positioning accuracy is ${\pm}13cm$, the average error on robot angle with the positioning is ${\pm}3$ degree.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.40 no.2
• /
• pp.1-9
• /
• 2003

We develop an experimental system to inspect a metal mask and, in this paper, introduce its inspection algorithm. This system is composed of an ASC(Area Scan Camera) and a belt type xy-table. The whole area of the metal mask is divided into several inspection blocks. The area of each block is equal to FOV(Field of View). For each block, the camera image is compared to the reference image. The reference image is made by gerber file. The rotation angle of the metal mask is calculated through the linear equation that is substituted two end points of horizontal boundary of a specific hole in a camera image. To calculate the position error caused by the belt type xy-table, HT(Hough-Transform) using distances among the holes in two images is used. The center of the reference image is moved as much as the calculated Position error to be coincided with the camera image. The information of holes in each image, such as centroid, size, width and height, are calculated through labeling. Whether a holes is mado correctly by laser machine or not, is judged by comparing the centroid and the size of hole in each image. Finally, we build the experimental system and apply this algorithm.

• Korean Journal of Remote Sensing
• /
• v.25 no.1
• /
• pp.45-59
• /
• 2009

This research presents the effect of Asian dust on the derived sea surface temperature (SST) from measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To analyze the effect, A VHRR infrared brightness temperature (TB) is estimated from simulated radiance calculated from radiative transfer model on various atmospheric conditions. Vertical profiles of temperature, pressure, and humidity from radiosonde observation are used to build up the East Asian atmospheric conditions in spring. Aerosol optical thickness (AOT) and size distribution are derived from skyradiation measurements to be used as inputs to the radiative transfer model. The simulation results show that single channel TB at window region is depressed under the Asian dust condition. The magnitude of depression is about 2K at nadir under moderate aerosol loading, but the magnitude reaches up to 4K at slant path. The dual channel difference (DCD) in spilt window region is also reduced under the Asian dust condition, but the reduction of DCD is much smaller than that shown in single channel TB simulation. Owing to the depression of TB, SST has cold bias. In addition, the effect of AOT on SST is amplified at large satellite zenith angle (SZA), resulting in high variance in derived SSTs. The SST depression due to the presence of Asian dust can be expressed as a linear function of AOT and SZA. On the basis of this relationship, the effect of Asian dust on the SST retrieval from the conventional daytime multi-channel SST algorithm can be derived as a function of AOT and SZA.

• Korean Journal of Applied Biomechanics
• /
• v.29 no.2
• /
• pp.43-51
• /
• 2019

Objective: This study aims to propose an efficient technical model through a kinematic analysis of field hockey drag flick shooting motion in laboratory situations and game situations and to build up the basic data on drag flick shooting technique through a comparative analysis of a Korean specialized shooter and specialized shooters of competing Asian countries. Method: This study selected one Korean female national specialized shooter and seven specialized shooters of competing countries, China, Japan, India, and Malaysia, who participated in the 2018 Asian Hockey Champions Trophy as research subjects. In exercise situations, a 3-D motion analysis utilizing an infrared camera was conducted, while in game situations, an image-based 3-D motion analysis utilizing a digital camera was conducted. Results: The Korean specialized shooter had smaller changes in the angles of the trunk and the stick in game situations than in exercise situations. She had a high angular velocity of the trunk and the stick head, and the maximum speed of the ball was high. The Korean specialized shooter had the maximum angular velocity of the trunk higher than the specialized shooters of the competing countries did, and the angular velocity of the stick head and the maximum speed of the ball were in the average level. Conclusion: As for drag flick shooting in game situations, changes in the angle of the trunk and the stick were small, and the angular velocity was high due to the pressure that the shooters should perform the motion fast with the defenders' interruptions, and this high angular velocity of the trunk and the stick head affected the movement of the ball. Thus, the maximum speed of the ball was higher in game situations than in exercise situations. The Korean specialized shooter had the maximum angular velocity higher than the specialized shooters of the competing countries did; however, the maximum speed of the ball was average, and it turned out that the maximum speed of the ball was associated with the angular velocity of the stick head in P3. Therefore, Korean specialized shooters need complementary training for a change to the torque of the stick head, using the strong torque of the trunk.

• Journal of Cadastre & Land InformatiX
• /
• v.52 no.1
• /
• pp.69-80
• /
• 2022

Drone photogrammetry generally acquires images vertically or obliquely from above, so when photographing for the purpose of three-dimensional modeling, image matching for the ground of a building and spatial accuracy of point cloud data are poor, resulting in poor 3D mesh completeness. Therefore, to overcome this, this study analyzed the spatial accuracy of each drone image by acquiring smartphone images from the ground, and evaluated the accuracy improvement and completeness of 3D mesh when the smartphone image is not combined with the drone image. As a result of the study, the horizontal (x,y) accuracy of drone photogrammetry was about 1/200,000, similar to that of traditional photogrammetry. In addition, it was analyzed that the accuracy according to the photographing method was more affected by the photographing angle of the object than the increase in the number of photos. In the case of the smartphone image combination, the accuracy was not significantly affected, but the completeness of the 3D mesh was able to obtain a 3D mesh of about LoD3 that satisfies the digital twin city standard. Therefore, it is judged that it can be sufficiently used to build a 3D model for digital twin city by combining drone images and smartphones or DSLR images taken on the ground.

• Journal of Radiation Protection and Research
• /
• v.14 no.1
• /
• pp.24-33
• /
• 1989

The peripheral dose, defined as the dose outside therapeutic photon fields, was estimated for 6MV X-ray linear accelerator. The measurements were performed using silicon diode detectors controlled by automatic controlled water phantom. The effects of field size, collimator position, presence or absence of wedge filter, and wedge angle were analyzed. The results were as follows 1. The peripheral dose decreases as the distance from field margin increases and it is more than 2.4% of central axis maximum dose even at 15cm distance from field margin. 2. Maximum build-up of peripheral dose is at 2-3 mm from the water surface and drops to a minimum at 1.5cm depth and then the dose increase again. 3. The peripheral dose increases as the field size. increases. At the short distance from field margin, the difference of peripheral dose between 5 $\times\;5cm^2$ and 20 $\times\;20cm^2$ field size reaches more than 2 fold. 4. The peripheral dose is higher along the upper collimator than along the lower collimator. The differences is less than 1%. 5. The presence of wedge filter increases peripheral dose. And the peripheral dose is higher along the blade side of wedge filter than along the ridge side. The difference is about 3% at 5cm distance from the field margin for 15 $\times\;15cm^2$ field size and 60$^{\circ}$ wedge filter. 6. The Peripheral dose of wedge filter increases as the wedge filter angle increases and the increasing ratio is about 2 fold in 60$^{\circ}$wedge filter compared with open field.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.4
• /
• pp.144-159
• /
• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.