• 제목/요약/키워드: discontinuity points

검색결과 52건 처리시간 0.021초

2차원과 3차원에서의 비정렬 동적 적응격자 형성법에 관한 연구 (A Dynamic Adaptation Technique on 2-D and 3-D Unstructured Meshes)

  • 박영민;오우섭;권오준
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2000년도 춘계 학술대회논문집
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    • pp.146-152
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    • 2000
  • Two and Three dimensional dynamic adaptation code is developed for transient computations. This code involves mesh refinement and coarsening to either add points in high gradient regions of flow or remove points where they are not needed, for high spatial accuracy. Temporary cell algorithm is used to maintain the original grid quality. To show the assessment of the accuracy and efficiency, two dimensional study and unsteady flows are computed. Also, three dimensional steady computations are made to assess the refinement using temporary cell algorithm. The result shows the high spatial accuracy primarily in discontinuity regions in steady and unsteady computation.

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그림조각 맞추기에 관한 연구 (A Study on the Jig - Saw Puzzle Matching)

  • 이동주;서일홍;오상록
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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    • pp.954-958
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    • 1988
  • A jig-saw puzzle matching technique is proposed. Specifically, the geometric patterns of the puzzle pieces are firstly extracted using a boundary tracking algorithm at low resolution. And then, features of the extracted pieces to describe jig-saw puzzle pieces such as angles and distances between corner points, and convexity or concavity of a corner point are obtained from some corner points implying discontinuity of curvature of puzzle pieces' boundary. Finally, a boundary matching algorithm without a priori information of matched puzzle is proposed.

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비선형 시스템 계통에서 신경망에 근거한 가변구조 제어 (Neural Network based Variable Structure Control for a Class of Nonlinear Systems)

  • 김현호;이천희
    • 정보처리학회논문지A
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    • 제8A권1호
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    • pp.56-62
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    • 2001
  • This paper presents a neural network based variable structure control scheme for nonlinear systems. In this scheme, a set of local variable structure control laws are designed on the basis of the linear models about preselected representative points which cover the range of the system operation of interest. From the combination of the set of local variable structure control laws, neural networks infer the approximate control input in between the operating points. The neural network based variable structure control alleviates the effects of model uncertainties, which cannot be compensated by the control techniques using feedback linearization. It also relaxes the discontinuity in the system’s behavior that appears when the control schemes based on the family of the linear models are applied to nonlinear systems. Simulation results of a ball and beam system, to which feedback linearization cannot be applied, demonstrate the feasibility of the proposed method.

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Design of a CT Saturation Detection Technique with the Countermeasure for a Spike Signal

  • Kang, Yong-Cheol;Yun, Jae-Sung
    • KIEE International Transactions on Power Engineering
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    • 제3A권2호
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    • pp.85-92
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    • 2003
  • When a current transformer (CT) is saturated, the wave-shape of the secondary current is distorted and contains points of inflection, which correspond to the start or end of each saturation period. Discontinuity in the first-difference function of the current arises at points of inflection, where the second and third differences convert into pulses that can be used to detect saturation. This paper describes the design and evaluation of a CT saturation detection technique using the third-difference function and includes the countermeasure for a spike signal. Test results clearly demonstrate that the algorithm successfully detects the start and end of each saturation period irrespective of the remanent flux and magnetization inductance in the saturated region. This paper concludes by describing the results of hardware implementation of the algorithm using a DSP.

가변 윈도우의 투영왜곡을 고려한 스테레오 정합 알고리듬 (A Stereo Matching Algorithm with Projective Distortion of Variable Windows)

  • 김경범;정성종
    • 대한기계학회논문집A
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    • 제25권3호
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    • pp.461-469
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    • 2001
  • Existing area-based stereo algorithms rely heavily on rectangular windows for computing correspondence. While the algorithms with the rectangular windows are efficient, they generate relatively large matching errors due to variations of disparity profiles near depth discontinuities and doesnt take into account local deformations of the windows due to projective distortion. In this paper, in order to deal with these problems, a new correlation function with 4 directional line masks, based on robust estimator, is proposed for the selection of potential matching points. These points is selected to consider depth discontinuities and reduce effects on outliers. The proposed matching method finds an arbitrarily-shaped variable window around a pixel in the 3d array which is constructed with the selected matching points. In addition, the method take into account the local deformation of the variable window with a constant disparity, and perform the estimation of sub-pixel disparities. Experiments with various synthetic images show that the proposed technique significantly reduces matching errors both in the vicinity of depth discontinuities and in continuously smooth areas, and also does not be affected drastically due to outlier and noise.

UAV-based bridge crack discovery via deep learning and tensor voting

  • Xiong Peng;Bingxu Duan;Kun Zhou;Xingu Zhong;Qianxi Li;Chao Zhao
    • Smart Structures and Systems
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    • 제33권2호
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    • pp.105-118
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    • 2024
  • In order to realize tiny bridge crack discovery by UAV-based machine vision, a novel method combining deep learning and tensor voting is proposed. Firstly, the grid images of crack are detected and descripted based on SE-ResNet50 to generate feature points. Then, the probability significance map of crack image is calculated by tensor voting with feature points, which can define the direction and region of crack. Further, the crack detection anchor box is formed by non-maximum suppression from the probability significance map, which can improve the robustness of tiny crack detection. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method in the Xiangjiang-River bridge inspection. Compared with the original tensor voting algorithm, the proposed method has higher accuracy in the situation of only 1-2 pixels width crack and the existence of edge blur, crack discontinuity, which is suitable for UAV-based bridge crack discovery.

개선된 정합 비용 및 시차 지도 재생성 기반 지역적 스테레오 정합 기법 (Local Stereo Matching Method based on Improved Matching Cost and Disparity Map Adjustment)

  • 강현련;윤인용;김중규
    • 전자공학회논문지
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    • 제54권5호
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    • pp.65-73
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    • 2017
  • 본 논문에서는 홀 영역과 시차 불연속 영역을 개선하기 위한 스테레오 정합 기법을 제안한다. 스테레오 정합 기법은 두 영상에서의 정합 점을 탐색하여 시차 지도를 추출한다. 하지만 기존의 스테레오 정합 기법들은 스테레오 영상의 베이스 라인 길이에 따라서 정확도와 정밀도가 반비례하는 문제점이 있다. 또한 영상의 폐색 영역과 특징 부족으로 인한 시차 불연속 영역이 존재한다. 제안한 기법에서는 개선된 AD-Census-Gradient 방법과 적응적 가중치 기반의 비용 결합을 통하여 불연속 영역과 오 정합 영역을 개선한 초기 시차 지도를 추출하였다. 그 후에 시차 지도 재생성 과정을 수행하여 오정합 영역을 개선함과 동시에 영상의 정밀도를 개선하였다. 실험 결과 제안하는 기법이 기존의 정합률이 높은 방법들과 비교하여 높은 수준의 정합률을 유지하면서 오정합 영역과 정밀도를 개선하였음을 보였다. 그리고 정합 오차율이 높은 영상의 경우, 최근에 발표된 스테레오 정합 방법들보다 정합 성능이 평균적으로 3.22(%)가량 증가하였다.

터널 막장 3차원 지형모델 상에서의 불연속면 자동 매핑을 위한 딥러닝 기법 적용 방안 (Deep Learning Approach for Automatic Discontinuity Mapping on 3D Model of Tunnel Face)

  • 추엔 팜;신휴성
    • 터널과지하공간
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    • 제33권6호
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    • pp.508-518
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    • 2023
  • 이 논문은 LiDAR 스캔 또는 사진측량 기술에 의해 재구성된 3D 디지털 모델을 기반으로 터널 벽면의 불연속면을 자동으로 매핑하는 새로운 접근 방식을 제안한다. 본 제안에서는 U-Net이라 불리는 딥러닝 시맨틱 영역분할 모델을 사용하며, 터널 막장면의 3D 지형 모델에서 불연속면 영역을 식별해 낸다. 제안된 딥러닝 모델은 투영된 RGB 이미지, 면의 깊이 이미지 및 국부적인 면의 표면 속성 이미지(즉, 법선 벡터 및 곡률 이미지)를 포함한 다양한 정보를 종합 학습하여 기본 3차원 이미지에서 불연속면 영역을 효과적으로 분할한다. 이후 영역분할 결과는 면의 깊이 맵과 투영 행렬을 사용하여 3D 모델로 다시 투영시키고, 3D 공간 내에서 불연속면의 위치 및 범위를 정확하게 표현한다. 영역분할 모델의 성능은 영역 분할된 결과를 해당 지면 실측 값과 비교함으로써 평가하였으며, IoU(intersection-over-union) 값이 약 0.8 정도로 나타나 영역분할 결과의 높은 정확성을 확인하였다. 여전히 학습데이터가 제한적 이었음에도 불구하고, 제안 기법은 3D 모델의 점군 데이터를 불연속면의 유사군으로 그룹화하기 위해 전 막장면의 법선 벡터와 클러스터링과 같은 비지도 학습기반 알고리즘에만 의존하던 기존 접근 방식의 한계의 극복 가능성을 보여주었다.

Characteristic wave detection in ECG using complex-valued Continuous Wavelet Transforms

  • Berdakh, Abibullaev;Seo, Hee-Don
    • 대한의용생체공학회:의공학회지
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    • 제29권4호
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    • pp.278-285
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    • 2008
  • In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

삼차원 구조 복원을 위한 스테레오 비전의 가변윈도우법 (A Variable Window Method for Three-Dimensional Structure Reconstruction in Stereo Vision)

  • 김경범
    • 한국정밀공학회지
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    • 제20권7호
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    • pp.138-146
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    • 2003
  • A critical issue in area-based stereo matching lies in selecting a fixed rectangular window size. Previous stereo methods doesn't deal effectively with occluding boundary due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper, a variable window approach is presented to estimate accurate, detailed and smooth disparities for three-dimensional structure reconstruction. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the three-dimensional disparity space. In addition, it investigates maximum connected match candidate points and then devise the novel arbitrarily shaped variable window representative of a same disparity to treat with disparity variations of various structure shapes. We demonstrate the performance of the proposed variable window method with synthetic images, and show how our results improve on those of closely related techniques for accuracy, robustness, matching density and computing speed.