• Title/Summary/Keyword: 다중 크기 검출

Search Result 104, Processing Time 0.023 seconds

항공기 구조 설계에서의 손상허용 해석

  • 권정호
    • Journal of the KSME
    • /
    • v.30 no.2
    • /
    • pp.131-140
    • /
    • 1990
  • 손상 허용 설계 개념의 목적은 항공기 성능의 최대 관건이 구조물 무게가 과도하게 증가하는 것 을 방지하고 동시에 충분한 신뢰도를 만족시키는데 있다. 이러한 테크놀로지의 설계 적용에 대하 여 몇 가지 중요한 점을 지적하면 결함 검사를 위하여 외부에서 접근이 용이하게 설계되어야 하 고 단일 하중 전달 구조에 비하여 다중 하중 전달 구조가 바람직한 것이다. 또한 해석적 방법에 대하여 충분한 시험으로 해석과정의 유효성이 인정되어야 하며 일반적으로 전체 구조의 수명을 위하여 재료의 인성치를 증가시키는 것보다 균열 검출 기술을 향상시켜 검출 가능 결함 크기를 낮추는 것이 효과적이라 할 수 있다.

  • PDF

Development of a Robust Multiple Audio Watermarking Using Improved Quantization Index Modulation and Support Vector Machine (개선된 QIM과 SVM을 이용한 공격에 강인한 다중 오디오 워터마킹 알고리즘 개발)

  • Seo, Ye-Jin;Cho, San-Gjin;Chong, Ui-Pil
    • Journal of the Institute of Convergence Signal Processing
    • /
    • v.16 no.2
    • /
    • pp.63-68
    • /
    • 2015
  • This paper proposes a robust multiple audio watermarking algorithm using improved QIM(quantization index modulation) with adaptive stepsize for different signal power and SVM(support vector machine) decoding model. The proposed algorithm embeds watermarks into both frequency magnitude response and frequency phase response using QIM. This multiple embedding method can achieve a complementary robustness. The SVM decoding model can improve detection rate when it is not sure whether the extracted data are the watermarks or not. To evaluate robustness, 11 attacks are employed. Consequently, the proposed algorithm outperforms previous multiple watermarking algorithm, which is identical to the proposed one but without SVM decoding model, in PSNR and BER. It is noticeable that the proposed algorithm achieves improvements of maximum PSNR 7dB and BER 10%.

Modular Neural Network Recognition System for Robot Endeffector Recognition (로봇 Endeffector 인식을 위한 다중 모듈 신경회로망 인식 시스템)

  • 신진욱;박동선
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.29 no.5C
    • /
    • pp.618-626
    • /
    • 2004
  • In this paper, we describe a robot endeffector recognition system based on a Modular Neural Networks (MNN). The proposed recognition system can be used for vision system which track a given object using a sequence of images from a camera unit. The main objective to achieve with the designed MNN is to precisely recognize the given robot endeffector and to minimize the processing time. Since the robot endeffector can be viewed in many different shapes in 3- D space, a MNN structure, which contains a set of feedforwared neural networks, can be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training MNN patterns for a neural network share the similar characteristics so that they can be easily trained. The trained UM is les s sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

Multi-scale Crack Detection Using Scaling (스케일링을 이용한 다중 스케일 균열 검출)

  • Kim, Young-Ro;Oh, Tae-Myung
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.50 no.9
    • /
    • pp.194-200
    • /
    • 2013
  • In this paper, we propose a multi-scale crack detection method using scaling. It is based on morphology algorithm, crack features, and scaling. We use a morphology operator which extracts patterns of crack. It segments cracks and background using opening and closing operations. Morphology based segmentation is better than existing integration methods using subtraction in detecting a crack it has small width. However, morphology methods using only one structure element could detect only fixed width crack. Thus, we use a scaling method. We use bilinear interpolation for scaling. Our method calculates values of properties such as the number of pixels and the maximum length of the segmented region. We decide whether the segmented region belongs to cracks according to those data. Experimental results show that our proposed multi-scale crack detection method has better results than those of existing detection methods.

The Intrusion sensor using the variations of speckle patterns (스페클 패턴을 이용한 침입자 센서)

  • Park, Jae Hui;Gang, Sin Won
    • Journal of the Institute of Electronics Engineers of Korea SD
    • /
    • v.38 no.3
    • /
    • pp.82-82
    • /
    • 2001
  • 스페클 패턴은 다중모드 광섬유 내를 전파하는 모드 사이의 간섭현상 때문에 발생하는 검은 무늬로서, 외부 섭동 (perturbation)의 크기에 따라 패턴이 바뀌게 된다. 이 현상을 이용하여 본 연구에서는 스페클 센서를 제작하여 실험을 통해 시설물을 원거리, 실시간 원격 감시가 가능하고 매우 민감한 침입자 센서로 응용 가능함을 확인하였다. 본 연구에서는 감도를 높이고 구조를 간단하게 하기 위해, 공간필터를 사용하는 대신 광검출기 홀더를 길이 가변이 가능하도록 지그를 제작하여 사용하였으며, 정류기와 FVC를 사용하여 외부 섭동의 지속시간과 크기를 알 수 있었다.

Analysis of Communication Performance According to Detection Sequence of MMSE Soft Decision Interference Cancellation Scheme for MIMO System (다중 입출력 시스템 MMSE 연판정 간섭 제거 기법의 검출 순서에 따른 통신 성능 분석)

  • Lee, Hee-Kwon;Kim, Deok-Chan;Kim, Tae-Hyeong;Kim, Yong-Kab
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.12 no.6
    • /
    • pp.636-642
    • /
    • 2019
  • In this paper, we analyzed BER (Bit Error Rate) communication performance according to the detection order of MMSE (Minimum Mean Square Error) based soft decision interference cancellation. As the detection order method, antenna index order method, absolute value magnitude order method of channel elements, absolute value sum order method of channel elements, and SNR (Signal Noise Ratio) order method are proposed. BER performance for the scheme was measured and analyzed. As a simulation environment, 16-QAM (Quadrature Amplitude Modulation) modulation is used in an uncoded environment of an M×M multiple-input multiple-output system, and an independent Rayleigh attenuation channel is considered. The simulation results show that the performance gain is about 1.5dB when the SNR-based detection order method is M=4, and the performance gain is about 3.5dB when M=8 and about 3.5dB when M=16. The more BER performance was confirmed, the more the detection order method of the received signal prevented the interference and error spreading occurring in the detection process.

Position Uncertainty due to Multi-scattering in the Scintillator Array of Dual Collimation Camera (복합 집속 카메라의 섬광체배열에서 다중산란에 의한 위치 불확실성)

  • Lee, Won-Ho
    • Journal of radiological science and technology
    • /
    • v.31 no.3
    • /
    • pp.287-292
    • /
    • 2008
  • Position information of radiation interactions in detection material is essential to reconstruct a radiation source image. With most position sensing techniques, the position information of a single interaction inside the detectors can be precisely obtained. Each interaction position of multi-scattering inside scintillators, however, can not be individually measured and only the average of the scattering positions can be obtained, which causes the uncertainty in the measured interaction position. In this paper, the position uncertainties due to the multi-scattering were calculated by Monte Carlo simulation. The simulation model was a 50 by 50 by 5 mm $LaCl_3$(Ce) scintillator(pixel size is 2 by 2 by 5mm) which was utilized for the dual collimation camera. The dual collimation camera uses the information from both photoelectric effect and Compton scattering, and therefore, position uncertainties for both partial and full energy deposition of radiation interactions are calculated. In the case of partial energy deposition(PED), the standard deviations of positions are less than $1{\sim}2mm$, which means the uncertainty caused by multi-scattering is not significant. Because the effect of the multi-scattering with PED is insignificant, the multi-scattering has little effect on the performance of Compton imaging of dual collimation camera. In the case of full energy deposition(FED), however, the standard deviation of the positions is about twice that of the pixel size of the 1stdetector, except for 122keV incident radiations. Therefore, the standard deviations caused by multi-scatterings should be considered in the design of the coded mask of the dual collimation camera to avoid artifact on the reconstructed image. The position uncertainties of the FEDs are much larger than those of the PEDs for all radiation energies and the ratio of PEDs to FEDs increases when the incident radiation energy increases. The position uncertainties of both PEDs and FEDs are dependent on the incident radiation energy.

  • PDF

Geant4를 이용한 STEIN 검출기의 입자 분리 검출 모의실험 예비 결과 분석

  • Park, Seong-Ha;Kim, Yong-Ho;U, Ju;Seon, Jong-Ho;Jin, Ho;Lee, Dong-Hun;Lin, Robert P.;Immel, Thomas
    • The Bulletin of The Korean Astronomical Society
    • /
    • v.37 no.2
    • /
    • pp.212.2-212.2
    • /
    • 2012
  • 지구 자기권에 존재하는 플라즈마 입자의 다중관측을 목적으로 개발된 초소형 탑재체 STEIN (SupraThermal Electron, Ion, Neutral) 은 경희대학교와 UC Berkeley가 공동으로 개발 중인 3대의 초소형 과학위성 TRIO-CINEMA (TRiplet Ionosphere Observatory - Cubesat for Ion, Neutral, Electron and MAgnetic fields) 에 탑재될 입자 검출기이다. 32개의 픽셀로 이루어진 STEIN 검출기는 2~300 keV의 전자, 4~300 keV의 이온과 중성입자(Energetic Neutral Atom: ENA) 를 분리 계측할 목적으로 설계되었으며, 하전입자가 정전장 편향기를 통과하여 서로 다른 검출기 픽셀에 도달함으로써 전자와 이온, 중성입자를 분리하여 계측할 수 있도록 하였다. 한편, STEIN 구조물에서 발생한 2차 입자의 검출을 방지하기 위해 정전 편향기 사이에 차단날(blade)을 설계하였다. 본 연구에서는 STEIN 모의실험 예비 결과로써 전기장에 크기 및 차단날에 의한 하전입자의 궤적과 이에 따른 분리 계측 성능을 알아보고자 Geant4 (GEometry ANd Tracking)를 사용하여 검출기 픽셀에 입사하는 전자의 초기 위치를 분석하였다. 전자의 입사 위치는 검출기로부터 5 cm 전방에서 6 mm * 20 mm 범위 내에서 무작위로 생성하여 검출기의 방향으로 수직 입사하였다. 분석 결과 전자들은 전기장의 방향에 따라 편향되는 결과를 보였으며, 저에너지 전자는 강한 전기장의 영향으로 차단날에 의해 차폐되어 검출되지 않았다. 따라서 전기장의 크기와 차단날에 따른 입자 분리 검출이 가능함을 본 모의실험을 통해 확인하였으며, STEIN 운용 시 입자 분리 검출 및 결과 분석 기반으로 본 연구 결과를 사용될 수 있을 것으로 기대된다.

  • PDF

A Real-time Face Recognition System using Fast Face Detection (빠른 얼굴 검출을 이용한 실시간 얼굴 인식 시스템)

  • Lee Ho-Geun;Jung Sung-Tae
    • Journal of KIISE:Software and Applications
    • /
    • v.32 no.12
    • /
    • pp.1247-1259
    • /
    • 2005
  • This paper proposes a real-time face recognition system which detects multiple faces from low resolution video such as web-camera video. Face recognition system consists of the face detection step and the face classification step. At First, it finds face region candidates by using AdaBoost based object detection method which have fast speed and robust performance. It generates reduced feature vector for each face region candidate by using principle component analysis. At Second, Face classification used Principle Component Analysis and multi-SVM. Experimental result shows that the proposed method achieves real-time face detection and face recognition from low resolution video. Additionally, We implement the auto-tracking face recognition system using the Pan-Tilt Web-camera and radio On/Off digital door-lock system with face recognition system.

Multi-scale face detector using anchor free method

  • Lee, Dong-Ryeol;Kim, Yoon
    • Journal of the Korea Society of Computer and Information
    • /
    • v.25 no.7
    • /
    • pp.47-55
    • /
    • 2020
  • In this paper, we propose one stage multi-scale face detector based Fully Convolution Network using anchor free method. Recently almost all state-of-the-art face detectors which predict location of faces using anchor-based methods rely on pre-defined anchor boxes. However this face detectors need to hyper-parameters and additional computation in training. The key idea of the proposed method is to eliminate hyper-parameters and additional computation using anchor free method. To do this, we apply two ideas. First, by eliminating the pre-defined set of anchor boxes, we avoid the additional computation and hyper-parameters related to anchor boxes. Second, our detector predicts location of faces using multi-feature maps to reduce foreground/background imbalance issue. Through Quantitative evaluation, the performance of the proposed method is evaluated and analyzed. Experimental results on the FDDB dataset demonstrate the effective of our proposed method.