• Title/Summary/Keyword: Calibration image

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Analysis of the Radiation Patterns of Satellite SAR System with Active-Transponder (능동전파반사기를 이용한 위성 SAR 시스템 방사 패턴 분석)

  • Hwang, Ji-Hwan;Kweon, Soon-Koo;Oh, Yisok
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.23 no.10
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    • pp.1204-1211
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    • 2012
  • Measurement and analysis results of the extracted radiation-patterns from the field-experiments which were conducted to acquire the generic technology for calibration and validation of the satellite SAR system(Synthetic Aperture Radar) are presented in this study. Prototype of active transponder is adjustable within maximum 63.1 dBsm of RCS (Radar Cross Section) and includes the receiving-function with external receiver. To increase an accuracy of these field experiments, we repetitively measured satellite SAR systems of the same operating mode(i.e., COSMO-SkyMed No. 2 & 3, hh-pol., strip-map himage mode, 3 m resolution). Then, the reliability of experimental results was cross-checked through analysis of the RCS of active transponder on SAR image. The property of azimuth radiation patterns of satellite SAR system extracted from them has $0.352^{\circ}$ of HPBW(half-power beamwidth), $0.691^{\circ}$ of FNBW(first-null beamwidth), and 11.17 dB of PSLR(peak to side lobe ratio), respectively.

Determination of 3D Object Coordinates from Overlapping Omni-directional Images Acquired by a Mobile Mapping System (모바일매핑시스템으로 취득한 중첩 전방위 영상으로부터 3차원 객체좌표의 결정)

  • Oh, Tae-Wan;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.3
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    • pp.305-315
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    • 2010
  • This research aims to develop a method to determine the 3D coordinates of an object point from overlapping omni-directional images acquired by a ground mobile mapping system and assess their accuracies. In the proposed method, we first define an individual coordinate system on each sensor and the object space and determine the geometric relationships between the systems. Based on these systems and their relationships, we derive a straight line of the corresponding object point candidates for a point of an omni-directional image, and determine the 3D coordinates of the object point by intersecting a pair of straight lines derived from a pair of matched points. We have compared the object coordinates determined through the proposed method with those measured by GPS and a total station for the accuracy assessment and analysis. According to the experimental results, with the appropriate length of baseline and mutual positions between cameras and objects, we can determine the relative coordinates of the object point with the accuracy of several centimeters. The accuracy of the absolute coordinates is ranged from several centimeters to 1 m due to systematic errors. In the future, we plan to improve the accuracy of absolute coordinates by determining more precisely the relationship between the camera and GPS/INS coordinates and performing the calibration of the omni-directional camera

Investigating Applicability of Unmanned Aerial Vehicle to the Tidal Flat Zone (조간대 갯벌에서 무인항공기 활용 가능성에 관한 연구 - 수치표고모델을 중심으로 -)

  • Kim, Bum-Jun;Lee, Yoon-Kyung;Choi, Jong-Kuk
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.461-471
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    • 2015
  • In this study, we generated orthoimages and Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) to confirm the accuracy of possibility of geospatial information system generation, then compared the DEM with the topographic height values measured from Real Time Kinematic-GPS (RTK-GPS). The DEMs were generated from aerial triangulation method using fixed-wing UAV and rotary-wing UAV, and DEM based on the waterline method also generated. For the accurate generation of mosaic images and DEM, the distorted images occurred by interior and exterior orientation were corrected using camera calibration. In addition, we set up the 30 Ground Control Points (GPCs) in order to correct of the UAVs position error. Therefore, the mosaic images and DEM were obtained with geometric error less than 30 cm. The height of generated DEMs by UAVs were compared with the levelled elevation by RTK-GPS. The value of R-square is closely 1. From this study, we could confirm that accurate DEM of the tidal flat can be generated using UAVs and these detailed spatial information about tidal flat will be widely used for tidal flat management.

Development of the Measurement Method of Extremely Low Level Activity with Imaging Plate (Imaging Plate를 이용한 극저준위 방사능 측정에 관한 연구)

  • Kwak, Ji-Yeon;Lee, K.B.;Lee, Jong-Man;Park, Tae-Soon;Oh, Pil-Jae;Lee, Min-Kie;Seo, Ji-Suk;Hwang, Han-Yull
    • Journal of Radiation Protection and Research
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    • v.29 no.4
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    • pp.231-236
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    • 2004
  • An imaging plate(IP) detector, a two-dimensional digital radiation detector that can acquire image of radioactivity distribution in a sample, has been applied in many fields; for industrial radiography, medical diagnosis, X-ray diffraction test, etc. In this study, the possibility of IP detector to be used lot measuring radioactivity of sample is explored using its high sensitivity, higher spatial resolution, wider dynamic range and screen uniformity for several kinds radiations. First, the IP detector is applied to measure the surface uniformity for area source. Surface uniformity is measured rapidly and nondestructively by measuring the radioactivity distribution of common standard area source$(^{241}Am)$. Next, the IP is employed to study the possibility of measuring an extremely low-level activity of environmental sample. For this study the screen uniformity, shield effect of background radiation, linear dynamic range and fading effect of the IP detector is investigated. The potato, banana, radish and carrot samples are chosen to measure ultra low-level activity of $^{40}K$ isotope. The efficiency calibration of IP detector is carried out using the standard source.

Measurements on Transient Mixing Concentrations of Two Fuel Oils using a Quantitative Flow Visualization Technique (정량적 유동가시화 기술을 이용한 이종연료유 과도 혼합 농도분포 측정)

  • Yum, Joo-Ho;Doh, Deog-Hee;Cho, Gyeong-Rae;Min, Seong-Ki;Kim, Myung-Ho;Ryu, Gyong-Won
    • Transactions of the Korean hydrogen and new energy society
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    • v.23 no.4
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    • pp.364-372
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    • 2012
  • Transient mixing states of two different fuel oils, dimethylformamide (DMF) oil and JetA1 oil, were investigated by using a color image processing and a neural network. A tank ($D{\times}H$, $310{\times}370mm$) was filled with JetA1 oil. The DMF oil was filled at a top tank, and was mixed with the JetA1 oil in the tank mixing tank via a sudden opening which was performed by nitrogen gas with 1.9 bar. An impeller was rotated with 700 rpm for mixing enhancements of the two fuel oils. To visualize the mixing state of the DMF oil with the JetA1 oil, the DMF oil was coated with Rhodamine B whose color was red. A LCD monitor was used for uniform illumination. The color changes of the DMF oil were captured by a camcoder and the images were transferred to a host computer for quantifying the information of color changes. The color images of two mixed oils were captured with the camcoder. The R, G, B color information of the captured images was used to quantify the concentration of the DMF oil. To quantify the concentration of the DMF oil in the JetA1 oil, a calibration of color-to-concentration was carried out before the main experiment was done. Transient mixing states of DMF oil with the JetA1 oil since after the sudden infiltration were quantified and characterized with the constructed visualization technique.

Stereo Vision based on Planar Algebraic Curves (평면대수곡선을 기반으로 한 스테레오 비젼)

  • Ahn, Min-Ho;Lee, Chung-Nim
    • Journal of KIISE:Software and Applications
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    • v.27 no.1
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    • pp.50-61
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    • 2000
  • Recently the stereo vision based on conics has received much attention by many authors. Conics have many features such as their matrix expression, efficient correspondence checking, abundance of conical shapes in real world. Extensions to higher algebraic curves met with limited success. Although irreducible algebraic curves are rather rare in the real world, lines and conics are abundant whose products provide good examples of higher algebraic curves. We consider plane algebraic curves of an arbitrary degree $n{\geq}2$ with a fully calibrated stereo system. We present closed form solutions to both correspondence and reconstruction problems. Let $f_1,\;f_2,\;{\pi}$ be image curves and plane and $VC_P(g)$ the cone with generator (plane) curve g and vertex P. Then the relation $VC_{O1}(f_1)\;=\;VC_{O1}(VC_{O2}(f_2)\;∩\;{\pi})$ gives polynomial equations in the coefficient $d_1,\;d_2,\;d_3$ of the plane ${\pi}$. After some manipulations, we get an extremely simple polynomial equation in a single variable whose unique real positive root plays the key role. It is then followed by evaluating $O(n^2)$ polynomials of a single variable at the root. It is in contrast to the past works which usually involve a simultaneous system of multivariate polynomial equations. We checked our algorithm using synthetic as well as real world images.

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A Study on the Estimation of Multi-Object Social Distancing Using Stereo Vision and AlphaPose (Stereo Vision과 AlphaPose를 이용한 다중 객체 거리 추정 방법에 관한 연구)

  • Lee, Ju-Min;Bae, Hyeon-Jae;Jang, Gyu-Jin;Kim, Jin-Pyeong
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.7
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    • pp.279-286
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    • 2021
  • Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

GEO-KOMPSAT-2A AMI Best Detector Select Map Evaluation and Update (천리안위성2A호 기상탑재체 Best Detector Select 맵 평가 및 업데이트)

  • Jin, Kyoungwook;Lee, Sang-Cherl;Lee, Jung-Hyun
    • Korean Journal of Remote Sensing
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    • v.37 no.2
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    • pp.359-365
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    • 2021
  • GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.

Comparison and Analysis of Matching DEM Using KOMPSAT-3 In/Cross-track Stereo Pair (KOMPSAT-3 In/Cross-track 입체영상을 이용한 매칭 DEM 비교 분석)

  • Oh, Kwan-Young;Jeong, Eui-Cheon;Lee, Kwang-Jae;Kim, Youn-Soo;Lee, Won-Jin
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1445-1456
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    • 2018
  • The purpose of this study is to compare the quality and characteristics of matching DEMs by using KOMPSAT-3 stereo pair capture in in-track and cross-track. For this purpose, two stereo pairs of KOMPSAT-3 were collected that were taken in the same area. The two stereo pairs have similar stereo geometry elements such as B/H, convergence angle. Sensor modeling for DEM production was performed with RFM affine calibration using multiple GCPs. The GCPs used in the study were extracted from the 0.25 m ortho-image and 5 meter DEM provided by NGII. In addition, matching DEMs were produced at the same resolution as the reference DEMs for a comparison analysis. As a result of the experiment, the horizontal and vertical errors at the CPs indicated an accuracy of 1 to 3 pixels. In addition, the shapes and accuracy of two DEMs produced in areas where the effects of natural or artificial surface land were low were almost similar.

Object Detection on the Road Environment Using Attention Module-based Lightweight Mask R-CNN (주의 모듈 기반 Mask R-CNN 경량화 모델을 이용한 도로 환경 내 객체 검출 방법)

  • Song, Minsoo;Kim, Wonjun;Jang, Rae-Young;Lee, Ryong;Park, Min-Woo;Lee, Sang-Hwan;Choi, Myung-seok
    • Journal of Broadcast Engineering
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    • v.25 no.6
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    • pp.944-953
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    • 2020
  • Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.