• Title/Summary/Keyword: 물체 크기

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Optical technique of precision measurement using Electronic Speckle Pattern Interferometry (ESPI를 이용한 광학식 정밀 계측 기술)

  • 은재정;정영환;최평석;박해수
    • Journal of the Institute of Convergence Signal Processing
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    • v.4 no.4
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    • pp.40-46
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    • 2003
  • In this research, we accomplished the interpreting about the vibration of the object, which is the out of plane displacement in the Electronic Speckle Pattern Interferometry(ESPI), one of the optical measuring technique. The vibrating object has a inherent nodal line, therefore we can get the information about the vibration of the object by interpreting it. we used a speaker and a cantilever plate for a measurement object, and interpreted it qualitatively by using the Time-Average ESPI. In this experimental result, the speaker has the lower mode of fringe at 550Hz, 570mV, and the higher mode of fringe at 950Hz, 570mV This ESPI is a non-destructive test, and because of using the laser at measuring, it has a high resolution. The ESPI can test vibration mode regardless of the test object size, because the area which illuminated laser is the test area.

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Intrusion Detection Algorithm based on Motion Information in Video Sequence (비디오 시퀀스에서 움직임 정보를 이용한 침입탐지 알고리즘)

  • Kim, Alla;Kim, Yoon-Ho
    • Journal of Advanced Navigation Technology
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    • v.14 no.2
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    • pp.284-288
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    • 2010
  • Video surveillance is widely used in establishing the societal security network. In this paper, intrusion detection based on visual information acquired by static camera is proposed. Proposed approach uses background model constructed by approximated median filter(AMF) to find a foreground candidate, and detected object is calculated by analyzing motion information. Motion detection is determined by the relative size of 2D object in RGB space, finally, the threshold value for detecting object is determined by heuristic method. Experimental results showed that the performance of intrusion detection is better one when the spatio-temporal candidate informations change abruptly.

Realization for Automatic Stock Cubic Measuring and Distributing Management Embedded System with 3D Ultrasonic Sensing (3D 초음파센싱 자동물류부피측정 및 분류관리 임베디드시스템 구현)

  • Lee, Eun-Eok;Ryu, Kwang-Rryol;Hur, Chang-Wu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.285-288
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    • 2007
  • A realization for automatic stock cubic measuring and distributing management embedded system with 3 dimensional ultrasonic sensing is presented in this paper. The height and width of cubic are measured by comparing the 3 values from 3 ultrasonic sensors with reference when an object is passing the conveyer and length is calculated by the passing time and velocity, compensate cubic values for error to vary with the environment temperature, and reduce the error by averaging the sensing data not to be right posture of object. The system enables to classify and load a packed stocks at the store and transportation practically based on the rectangular hexahedral objects.

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The motion estimation algorithm implemented by the color / shape information of the object in the real-time image (실시간 영상에서 물체의 색/모양 정보를 이용한 움직임 검출 알고리즘 구현)

  • Kim, Nam-Woo;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2733-2737
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    • 2014
  • Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

Prediction of burial depth over time evolution at seabed (해저면에서 시간변화에 따른 매몰심 변화 예측)

  • Seungho Lee;Hyoseob Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.476-476
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    • 2023
  • 해저면에 놓인 물체는 주변의 국소 흐름 변화에 의해 해저면 전단응력이 국부적으로 변화하는 과정에서 침식과 퇴적이 발생하게 되면서 해저면 지형의 변화에 의해 움직임이 발생한다. 이때 물체의 크기, 무게, 밀도와 형상에 따라 구름, 미끄러짐, 액상화 현상 또한 동반 될 수 있다. 본 연구에서는 해저면에 놓인 물체의 시간변화에 따른 매몰심 변화를 예측하고자 하였다. 물체는 원형 단면의 실린더 형태로 고려했다. 시간변화에 따른 매몰심 변화를 평형 매몰심으로의 접근속도에 관련된 인수와 매몰심 변화량으로 기본방적식을 구성하였고, 이를 유한 차분식으로 수립하였다. 최종 평형 매몰심 계산은 Friedrichs et al.(2016)의 경험식을 사용하였다. 앞선 연구에서 김효섭 등(2016)은 시간에 따른 세굴심 변화 모델 STEP-K를 제시한 바 있다. 시간변화에 따른 연직방향 실린더 주변에서의 국소세굴심을 예측하는 기법으로, 해저면에 놓인 수평방향 물체 주변의 매몰심 발달을 예측하기 위해 매몰 발생에 대한 시간의 척도를 새롭게 제안하였다. STEP-K에서 사용했던 KC수를 대신해 흐름-단주기 파랑 공조시의 해저면의 전단응력을 대표할 수 있는 대표전단응력을 사용할 수 있게 하였다. 보정계수를 통해 현장 또는 실험실 단위의 자료가 가용한 경우 식을 보정할 수 있다. 제안한 매몰심 예측기법은 Elmore et al.(2007)의 매몰실험 관측자료를 활용하여 보정하였다. 결과적으로 보정자료에 대한 시간에 따른 매몰심의 변화양상을 잘 재현하였으며, 향후 우리나라 해양환경 자료를 활용한 보정을 통해 적용성을 높일 수 있을 것으로 기대된다.

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Stereo Object Tracking System using Multiview Image Reconstruction Scheme (다시점 영상복원 기법을 이용한 스테레오 물체추적 시스템)

  • Ko, Jung-Hwan;Ohm, Woo-Young
    • 전자공학회논문지 IE
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    • v.43 no.2
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    • pp.54-62
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    • 2006
  • In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Basing on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having $256\times256$ pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05 % on average between the detected and actual location coordinates of the target object.

Stereo Object Tracking and Multiview image Reconstruction System Using Disparity Motion Vector (시차 움직임 벡터에 기반한 스데레오 물체추적 및 다시점 영상복원 시스템)

  • Ko Jung-Hwan;Kim Eun-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.2C
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    • pp.166-174
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    • 2006
  • In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Being based on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having 256$\times$256 pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05$\%$ on average between the detected and actual location coordinates of the target object.

Carrying pose optimization by using wrench space (렌치 스페이스를 이용한 물체 들기 자세 최적화)

  • Choi, Myung Geol
    • Journal of the Korea Computer Graphics Society
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    • v.21 no.4
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    • pp.19-26
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    • 2015
  • This paper presents a method for optimizing a carrying pose of human body for a given object. The inputs are articulated human body model and and arbitrary-shaped object. We assume that the object is big and heavy, so that both arms should be used to carry it. Unlike small and light objects, big and heaby objects can be hold by only a small range of body poses while keeping a physical statbility. We first introduce an algorithm that evaluates a physical stability of a given human body pose and object state (position and orientation). Then, we define a configuration space and search the space for the most stable carrying pose by using the evaluation algorithm. Finally, to demonstrate the usability of our method, we present the results which each is experimented with different shaped objects and additional user conditions.

32-Channel Bioimpedance Measurement System for the Detection of Anomalies with Different Resistivity Values (저항률이 다른 내부 물체의 검출을 위한 32-채널 생체 임피던스 측정 시스템)

  • 조영구;우응제
    • Journal of Biomedical Engineering Research
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    • v.22 no.6
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    • pp.503-510
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    • 2001
  • In this paper. we describe a 32-channel bioimpedance measurement system It consists of 32 independent constant current sources of 50 kHz sinusoid. The amplitude of each current source can be adjusted using a 12-bit MDAC. After we applied a pattern of injection currents through 32 current injection electrodes. we measured induced boundary voltages using a variable-gain narrow-band instrumentation amplifier. a Phase-sensitive demodulator. and a 12-bit ADC. The system is interfaced to a PC for the control and data acquisition. We used the system to detect anomalies with different resistivity values in a saline Phantom with 290mm diameter The accuracy of the developed system was estimated as 2.42% and we found that anomalies larger than 8mm in diameter can be detected. We Plan to improve the accuracy by using a digital oscillator improved current sources by feedback control, Phase-sensitive A/D conversion. etc. to detect anomalies smaller than 1mm in diameter.

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(Searching Effective Network Parameters to Construct Convolutional Neural Networks for Object Detection) (물체 검출 컨벌루션 신경망 설계를 위한 효과적인 네트워크 파라미터 추출)

  • Kim, Nuri;Lee, Donghoon;Oh, Songhwai
    • Journal of KIISE
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    • v.44 no.7
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    • pp.668-673
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    • 2017
  • Deep neural networks have shown remarkable performance in various fields of pattern recognition such as voice recognition, image recognition and object detection. However, underlying mechanisms of the network have not been fully revealed. In this paper, we focused on empirical analysis of the network parameters. The Faster R-CNN(region-based convolutional neural network) was used as a baseline network of our work and three important parameters were analyzed: the dropout ratio which prevents the overfitting of the neural network, the size of the anchor boxes and the activation function. We also compared the performance of dropout and batch normalization. The network performed favorably when the dropout ratio was 0.3 and the size of the anchor box had not shown notable relation to the performance of the network. The result showed that batch normalization can't entirely substitute the dropout method. The used leaky ReLU(rectified linear unit) with a negative domain slope of 0.02 showed comparably good performance.