• Title/Summary/Keyword: Signal processing

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A Study on the Enhancement of DEM Resolution by Radar Interferometry (레이더 간섭기법을 이용한 수치고도모델 해상도 향상에 관한 연구)

  • Kim Chang-Oh;Kim Sang-Wan;Lee Dong-Cheon;Lee Yong-Wook;Kim Jeong Woo
    • Korean Journal of Remote Sensing
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    • v.21 no.4
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    • pp.287-302
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    • 2005
  • Digital Elevation Models (DEMs) were generated by ERS-l/2 and JERS-1 SAR interferometry in Daejon area, Korea. The quality of the DEM's was evaluated by the Ground Control Points (GCPs) in city area where GCPs were determined by GPS surveys, while in the mountain area with no GCPs, a 1:25,000 digital map was used. In order to minimize errors due to the inaccurate satellite orbit information and the phase unwrapping procedure, a Differential InSAR (DInSAR) was implemented in addition to the traditional InSAR analysis for DEM generation. In addition, DEMs from GTOPO30, SRTM-3, and 1:25,000 digital map were used for assessment the resolution of the DEM generated from DInSAR. 5-6 meters of elevation errors were found in the flat area regardless of the usage and the resolution of DEM, as a result of InSAR analyzing with a pair of ERS tandem and 6 pairs of JERS-1 interferograms. In the mountain area, however, DInSAR with DEMs from SRTM-3 and the digital map was found to be very effective to reduce errors due to phase unwrapping procedure. Also errors due to low signal-to-noise ratio of radar images and atmospheric effect were attenuated in the DEMs generated from the stacking of 6 pairs of JERS-1. SAR interferometry with multiple pairs of SAR interferogram with low resolution DEM can be effectively used to enhance the resolution of DEM in terms of data processing time and cost.

Velocity Distribution Measurements in Mach 2.0 Supersonic Nozzle using Two-Color PIV Method (Two Color PIV 기법을 이용한 마하 2.0 초음속 노즐의 속도분포 측정)

  • 안규복;임성규;윤영빈
    • Journal of the Korean Society of Propulsion Engineers
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    • v.4 no.4
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    • pp.18-25
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    • 2000
  • A two-color particle image velocimetry (PIV) has been developed for measuring two dimensional velocity flowfields and applied to a Mach 2.0 supersonic nozzle. This technique is similar to a single-color PIV technique except that two different color laser beams are used to solve the directional ambiguity problem. A green-color laser sheet (532 nm: 2nd harmonic beam of YAG laser) and a red-color laser sheet (619 nm: output beam from YAG pumped Dye laser using Rhodamine 640) are employed to illuminate the seeded particles. A high resolution (3060${\times}$2036) digital color CCD camera is used to record the particle positions. This system eliminates the photographic-film processing time and subsequent digitization time as well as the complexities associated with conventional image shifting techniques for solving directional ambiguity problem. The two-color PIV also has the advantage that velocity distributions in high speed flowfields can be measured simply and accurately by varying the time interval between two different laser beams due to its high signal-to-noise ratio and thereby less requirement of panicle pair numbers for a velocity vector in one interrogation spot. The velocity distribution in the Mach 2.0 supersonic nozzle has been measured and the over-expanded shock cell structure can be predicted by the strain rate field. These results are compared and analyzed with the schlieren photograph for the velocity distributions and shock location.

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A Study on Maximizing the Matching Ratio of Scintillation Pixels and Photosensors of PET Detector using a Small Number of Photosensors (적은 수의 광센서를 사용한 PET 검출기의 섬광 픽셀과 광센서 매칭 비율의 최대화 연구)

  • Lee, Seung-Jae;Baek, Cheol-Ha
    • Journal of the Korean Society of Radiology
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    • v.15 no.5
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    • pp.749-754
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    • 2021
  • In order to maximize the matching ratio between the scintillation pixel and the photosensor of the PET detector using a small number of photosensor, various arrays of scintillation pixels and four photosensors were used. The array of scintillation pixels consisted of six cases from 6 × 6 to 11 × 11. The distance between the photosensors was applied equally to all scintillation pixels, and the arrangement was expanded by reducing the size of scintillation pixel. DETECT2000 capable of light simulation was used to acquire flood images of the designed PET detectors. At the center of each scintillation pixel array, light generated through the interaction between extinction radiation and scintillation pixels was generated, and the light was detected through for four photosensors, and then a flood image was reconstructed. Through the reconstructed flood image, we found the largest arrangement in which all the scintillation pixels can be distinguished. As a result, it was possible to distinguish all the scintillation pixels in the flood image of 8 × 8 scintillation pixel array, and from the 9 × 9 scintillation pixel flood image, the two edge scintillation pixels overlapped and appeared in the image. At this time, the matching ratio between the scintillation pixel and the photosensor was 16:1. When a PET system is constructed using this detector, the number of photosensors used is reduced and the cost of the oveall system is expected to be reduced through the simplification of the signal processing circuit.

A Problematic Bubble Detection Algorithm for Conformal Coated PCB Using Convolutional Neural Networks (합성곱 신경망을 이용한 컨포멀 코팅 PCB에 발생한 문제성 기포 검출 알고리즘)

  • Lee, Dong Hee;Cho, SungRyung;Jung, Kyeong-Hoon;Kang, Dong Wook
    • Journal of Broadcast Engineering
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    • v.26 no.4
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    • pp.409-418
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    • 2021
  • Conformal coating is a technology that protects PCB(Printed Circuit Board) and minimizes PCB failures. Since the defects in the coating are linked to failure of the PCB, the coating surface is examined for air bubbles to satisfy the successful conditions of the conformal coating. In this paper, we propose an algorithm for detecting problematic bubbles in high-risk groups by applying image signal processing. The algorithm consists of finding candidates for problematic bubbles and verifying candidates. Bubbles do not appear in visible light images, but can be visually distinguished from UV(Ultra Violet) light sources. In particular the center of the problematic bubble is dark in brightness and the border is high in brightness. In the paper, these brightness characteristics are called valley and mountain features, and the areas where both characteristics appear at the same time are candidates for problematic bubbles. However, it is necessary to verify candidates because there may be candidates who are not bubbles. In the candidate verification phase, we used convolutional neural network models, and ResNet performed best compared to other models. The algorithms presented in this paper showed the performance of precision 0.805, recall 0.763, and f1-score 0.767, and these results show sufficient potential for bubble test automation.

Waveform Decomposition of Airborne Bathymetric LiDAR by Estimating Potential Peaks (잠재적 피크 추정을 통한 항공수심라이다 웨이브폼 분해)

  • Kim, Hyejin;Lee, Jaebin;Kim, Yongil;Wie, Gwangjae
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1709-1718
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    • 2021
  • The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.

Dual CNN Structured Sound Event Detection Algorithm Based on Real Life Acoustic Dataset (실생활 음향 데이터 기반 이중 CNN 구조를 특징으로 하는 음향 이벤트 인식 알고리즘)

  • Suh, Sangwon;Lim, Wootaek;Jeong, Youngho;Lee, Taejin;Kim, Hui Yong
    • Journal of Broadcast Engineering
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    • v.23 no.6
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    • pp.855-865
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    • 2018
  • Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

Analysis of Magnetic Flux Leakage based Local Damage Detection Sensitivity According to Thickness of Steel Plate (누설자속 기반 강판 두께별 국부 손상 진단 감도 분석)

  • Kim, Ju-Won;Yu, Byoungjoon;Park, Sehwan;Park, Seunghee
    • Journal of Korean Society of Disaster and Security
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    • v.11 no.2
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    • pp.53-60
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    • 2018
  • To diagnosis the local damages of the steel plates, magnetic flux leakage (MFL) method that is known as a adaptable non-destructive evaluation (NDE) method for continuum ferromagnetic members was applied in this study. To analysis the sensitivity according to thickness of steel plate in MFL method based damage diagnosis, several steel plate specimens that have different thickness were prepared and three depths of artificial damage were formed to the each specimens. To measured the MFL signals, a MFL sensor head that have a constant magnetization intensity were fabricated using a hall sensor and a magnetization yoke using permanent magnets. The magnetic flux signals obtained by using MFL sensor head were improved through a series of signal processing methods. The capability of local damage detection was verified from the measured MFL signals from each damage points. And, the peak to peak values (P-P value) extracted from the detected MFL signals from each thickness specimen were compared each other to analysis the MFL based local damage detection sensitivity according to the thickness of steel plate.

Performance Enhancement of Differential Power Analysis Attack with Signal Companding Methods (신호 압신법을 이용한 차분전력분석 공격성능 향상)

  • Ryoo, Jeong-Choon;Han, Dong-Guk;Kim, Sung-Kyoung;Kim, Hee-Seok;Kim, Tae-Hyun;Lee, Sang-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.2
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    • pp.39-47
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    • 2008
  • Among previous Side Channel Analysis (SCA) methods, Differential Power Analysis (DPA) based on the statistical characteristics of collected signals has been known as an efficient attack for uncovering secret key of cryptosystems. However, the attack performance of this method is affected very much by the temporal misalignment and noise of collected side channel signals. In this paper, we propose a new method to surmount the noise problem in DPA. The performance of the proposed method is then evaluated while analyzing the power consumption signals of Micro-controller chips during a DES operation. Its performance is then compared to that of the original DPA in the time and frequency domains. When we compare the experimental results with respect to the needed number of traces to uncover the secret key, our proposed method shows the performance enhancement 33% in the time domain and 50% in the frequency domain.

Development of High Energy X-ray Dose Measuring Device based Ion Chamber for Cargo Container Inspection System (이온전리함 기반의 컨테이너 검색용 고에너지 X-선 선량 측정장치 개발)

  • Lee, Junghee;Lim, Chang Hwy;Park, Jong-Won;Lee, Sang Heon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1711-1717
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    • 2020
  • X-ray of up to 9MeV are used for container inspection. X-ray intensity must be maintained stably regardless of changes in time. If dose is not constant, it may affect the image quality, and as a result, may affect the inspection of abnormal cargo. Therefore, to acquire high-quality images, continuous dose monitoring is required. In this study, the ion-chamber based device was developed for monitoring the dose change in high-energy x-ray. And to estimate the performance of signal-processing device change according to the environmental change, the output changing due to the change of temperature and humidity was observed. In addition, verification of the device was performed by measuring the output change. As a result of the measurement, there was no significant difference in performance due to changes in temperature and humidity, and the change in output according to the change in exposure was linear. Therefore, it was found that the developed device is suitable for the dose monitoring of high-energy x-ray.

A Study on Possibility of Improvement of MIR Brightness Temperature Bias Error of KOMPSAT-3A Using GEOKOMPSAT-2A (천리안2A호를 이용한 다목적실용위성3A호 중적외선 밝기 온도 편향오차 개선 가능성 연구)

  • Kim, HeeSeob
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.48 no.12
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    • pp.977-985
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    • 2020
  • KOMPSAT-3A launched in 2015 provides Middle InfraRed(MIR) images with 3.3~5.2㎛. Though the satellite provide high resolution images for estimating bright temperature of ground objects, it is different from existing satellites developed for natural science purposes. An atmospheric compensation process is essential in order to estimate the surface brightness temperature from a single channel MIR image of KOMPSAT-3A. However, even after the atmospheric compensation process, there is a brightness temperature error due to various factors. In this paper, we analyzed the cause of the brightness temperature estimation error by tracking signal flow from camera physical characteristics to image processing. Also, we study on possibility of improvement of MIR brightness temperature bias error of KOMPSAT-3A using GEOKOMPSAT-2A. After bias compensation of a real nighttime image with a large bias error, it was confirmed that the surface brightness temperature of KOMPSAT-3A and GEOKOMPSAT-2A have correlation. We expect that the GEOKOMPSAT-2A images will be helpful to improve MIR brightness temperature bias error of KOMPSAT-3A.