• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.2
• /
• pp.69-76
• /
• 2020

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.292-292
• /
• 2016

논의 배수특성 분석은 물꼬 크기 및 개소수, 배수로 구성, 규모, 경사, 재질 등과 같은 물리적 특성 인자들의 영향으로 인해 일반적인 유역의 홍수량 산정을 위해 사용되는 수문학적 홍수추적 방법의 적용이 어렵다. 따라서 논에서의 유출을 모의하기 위해서는 수리학적 홍수추적 방법의 적용이 필요하며, 기존의 연구들은 대부분 1차원과 2차원의 수치 해석 기법으로 논의 유출 특성을 분석해왔다. 3차원 수치 해석 기법을 적용할 경우 1차원과 2차원에서 볼 수 없는 유동 특성 등을 파악할 수 있으며, 보다 정확한 유출 모의가 가능할 것으로 기대된다. 하지만 3차원 해석은 비교적 구조가 단순한 논에 적용하기에는 시간과 비용이 과도하게 소모된다는 단점이 있다. 한편, 상사법칙은 주로 실험의 스케일을 줄이기 위해 적용되어 왔다. 정확성에 대한 검증이 이루어진다면, 시간이 오래 걸리는 3차원 모델링에 상사법칙을 적용할 경우, 모의 시간을 단축시킬 수 있는 장점이 있을 것으로 사료된다. 따라서 본 연구에서는 3차원 수치 해석 모형인 FLOW-3D를 이용하여 논에서의 유출을 모의하고, 적용성을 평가하고자 한다. 또한 상사법칙을 이용하여 모의 시간을 단축할 수 있는 방법을 제시하고자 한다. 모의 대상으로 40m x 100m의 논 포장을 구성하였으며, 강우 및 관개에 따른 유출을 모의하였다. 모의 결과는 실측치 및 기존 연구의 결과와 비교하여 적용성을 평가하였다. 또한 수리학적 상사법칙을 적용하여 조건을 변화시켜가며 유출을 모의하였고, 모의 조건 및 모의 시간 변화에 따른 정확성을 분석하였다. 본 연구에서 제시한 방법은 논에서의 유출 모의의 정확성을 향상 시켜, 홍수 발생 시 농경지의 침수 대책 마련에 기여할 수 있을 것으로 기대된다.

• Journal of Convergence for Information Technology
• /
• v.8 no.6
• /
• pp.135-142
• /
• 2018

In recent years, researches utilizing UAV for military purposes such as precision tracking and batting have been actively conducted. In order to track the preceding flight, there has been a previous research on estimating the attitude information of the flight such as roll, pitch, and yaw using images taken from the rear UAV. In this study, we propose a method to estimate the attitude information more precisely by applying the Kalman filter to the existing image processing technique. By applying the Kalman filter to the estimated attitude data using image processing, we could reduce the estimation error of the attitude angle significantly. Through the simulation experiments, it was confirmed that the estimation using the Kalman filter can estimate the posture information of the aircraft more accurately.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.25-41
• /
• 2024

For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.4
• /
• pp.723-730
• /
• 2015

In this paper, a location tracking compensation algorithm based on the Least-Squares Method ($LCA_{LSM}$) was proposed to improve the autonomous tracking efficiency for the docent robot in exhibition hall, and the performance of the $LCA_{LSM}$ is analyzed by several practical experiments. The proposed $LCA_{LSM}$ compensates the collected location coordinates for the robot using the Least-Squares Method (LSM) in order to reduce the cumulated errors that occur in the Encoder/Giro sensor (E/G) and to enhance the measured tracking accuracy rates in the autonomous tracking of the robot in exhibition hall. By experiments, it was confirmed that the average error reduction rates of the $LCA_{LSM}$ are higher as 4.85% than that of the $LCA_{KF}$ in Scenario 1 (S1) and Scenario 2 (S2), respectively on the location tracking. In addition, it was also confirmed that the standard deviation in the measured errors of the $LCA_{LSM}$ are much more low and constant compared to that of the E/G sensor and the $LCA_{KF}$ in S1 and S2 respectively. Finally, we see that the suggested $LCA_{LSM}$ can execute more the stabilized location tracking than the E/G sensors and the $LCA_{KF}$ on the straight lines of S1 and S2 for the docent robot.

• Journal of Korean Society of Transportation
• /
• v.26 no.4
• /
• pp.173-184
• /
• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_1
• /
• pp.763-774
• /
• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• The KIPS Transactions:PartC
• /
• v.19C no.3
• /
• pp.209-214
• /
• 2012

Time synchronization is important role in a network, especially in Wireless Sensor Network (WSN) which is required for time-critical applications such as surveillance, tracking, data fusion and scheduling. Time synchronization in WSN should meet the other different requirements than the one in other networks because WSN has critical resource constraints, especially power consumption. This paper presents a new time synchronization scheme for WSN, which is energy efficient by reducing communication overhead. Simulation test shows this new scheme has better energy efficiency and performance of accuracy than existing schemes proposed previously.

• Convergence Security Journal
• /
• v.6 no.3
• /
• pp.37-47
• /
• 2006

In this research, We connect the terrestrial magnetism sensor of the Philips to a bluetooth communication system and measured 360 degree of the azimuth change the angle with an incline of 5 degrees to an order direction. The value of the azimuth to be measured sent to the Bluetooth communication system and analyzed the measuring value in the 100m as moved. Using the bluetooth, we could send the measuring value of the azimuth without the bearing error in the plain without an electric wave obstacle within a distance in straight line 100M. We got the value of the azimuth have 98% reliability to maintain at a level with the terrestrial magnetism sensor. Based on this research. We send the measuring value of the azimuth which the accuracy is improved to a mobile intelligent robot moving a land inclined equipped with this system and can track the azimuth of it.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.3C
• /
• pp.125-132
• /
• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about 5°horizontally and 8°vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.