• 제목/요약/키워드: multi-scale method

검색결과 812건 처리시간 0.028초

다중 스케일 영상 공간에서 특징점 클러스터를 이용한 영상스케일 예측 (Image Scale Prediction Using Key-point Clusters on Multi-scale Image Space)

  • 류권열
    • 융합신호처리학회논문지
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    • 제19권1호
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    • pp.1-6
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    • 2018
  • 본 논문에서는 다중 스케일 영상 공간에서 특징점 검출을 위해 수행되는 반복적인 과정을 제거하는 방법을 제안한다. 제안한 방법은 원 영상으로부터 특징점을 검출하고, 클러스터 필터를 이용하여 유효한 특징점을 선별하고, 특징점 클러스터를 생성한다. 그리고 특징점 클러스터의 방향 각도를 이용하여 참조 객체를 선별하고, 분산 거리 비율을 이용하여 원 영상의 스케일을 예측한다. 예측한 스케일에 따라 참조 영상의 스케일을 변환하고, 변환된 참조 영상에 대해 특징점 검출을 적용한다. 실험 결과 제안한 방법은 다중 스케일 영상을 사용하는 SIFT 방법 및 Scaled ORB 방법에 비해 특징점 검출 시간이 각각 75% 및 71% 향상됨을 알 수 있었다.

해체와 구성을 이용한 다중 스케일 균열 검출 (Multi-scale crack detection using decomposition and composition)

  • 김영로;정지영
    • 디지털산업정보학회논문지
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    • 제9권3호
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    • pp.13-20
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    • 2013
  • In this paper, we propose a multi-scale crack detection method. This method uses decomposition, composition, and shape properties. It is based on morphology algorithm, crack features. 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 decomposition and composition methods. We use a decimation method for decomposition. After decomposition and morphology operation, we get edge images given by binary values. 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.

Investigation of elasto-plastic seismic response analysis method for complex steel bridges

  • Tang, Zhanzhan;Xie, Xu;Wang, Yan;Wang, Junzhe
    • Earthquakes and Structures
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    • 제7권3호
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    • pp.333-347
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    • 2014
  • Multi-scale model can take both computational efficiency and accuracy into consideration when it is used to conduct elasto-plastic seismic response analysis for complex steel bridges. This paper proposed a method based on pushover analysis of member sharing the same section pattern to verify the accuracy of multi-scale model. A deck-through type steel arch bridge with a span length of 200m was employed for seismic response analysis using multi-scale model and fiber model respectively, the validity and necessity of elasto-plastic seismic analysis for steel bridge by multi-scale model was then verified. The results show that the convergence of load-displacement curves obtained from pushover analysis for members having the same section pattern can be used as a proof of the accuracy of multi-scale model. It is noted that the computational precision of multi-scale model can be guaranteed when length of shell element segment is 1.40 times longer than the width of section where was in compression status. Fiber model can only be used for the predictions of the global deformations and the approximate positions of plastic areas on steel structures. However, it cannot give exact prediction on the distribution of plastic areas and the degree of the plasticity.

Experiment and simulation analysis on full scale double-layer concrete shell

  • Thanh Quang Khai Lam;Thi My Dung Do
    • Computers and Concrete
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    • 제31권1호
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    • pp.9-21
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    • 2023
  • The published studies usually used analytical method, numerical methods or experimental method to determine the stress-strain state and displacement of the single-layer or multi-layer curved shell types, but with a small scale model. However, a full scale multi-layer doubly curved concrete shell roof model should be researched. This paper presents the results of the experiment and simulation analysis involving stress-strain state, sliding between layers, the formation and development of the full scale double-layer doubly curved concrete shell roof when this shell begins to crack. The results of the this study have constructed the load-sliding strain relationship; strain diagram; stress diagram in the shell layers; the Nx, Ny membrane force diagram and deflection of shell. Thisresults by experimental method on a full scale model of concrete have clarified the working of multi-layer doubly curved concrete shell roof. The experimental and simulation results are compared with each other and compared with the Sap2000 software.

ED-FEM multi-scale computation procedure for localized failure

  • Rukavina, Ivan;Ibrahimbegovic, Adnan;Do, Xuan Nam;Markovic, Damijan
    • Coupled systems mechanics
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    • 제8권2호
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    • pp.111-127
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    • 2019
  • In this paper, we present a 2D multi-scale coupling computation procedure for localized failure. When modeling the behavior of a structure by a multi-scale method, the macro-scale is used to describe the homogenized response of the structure, and the micro-scale to describe the details of the behavior on the smaller scale of the material where some inelastic mechanisms, like damage or plasticity, can be defined. The micro-scale mesh is defined for each multi-scale element in a way to fit entirely inside it. The two scales are coupled by imposing the constraint on the displacement field over their interface. An embedded discontinuity is implemented in the macro-scale element to capture the softening behavior happening on the micro-scale. The computation is performed using the operator split solution procedure on both scales.

일본내 연구동향 (6편중 제4편) (State-of-the-art of the multi-scale analysis of advanced composite materials by homogenization method)

  • Takano, Naoki
    • Composites Research
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    • 제15권5호
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    • pp.44-52
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    • 2002
  • To study numerically the mechanical behaviors of advanced composite materials considering the microscopic phenomena as well as the macroscopic properties and behaviors, a multi-scale modeling and analysis by the mathematical homogenization method with the help of the finite element method(FEM) are reviewed. The hierarchical modeling strategy and the formulation are briefly described first to give some idea of the multi-scale framework. The latter half of this article focuses on the verification of the multi-scale analysis by the homogenization method in its applications to real advanced materials. The first example is the verification of the predicted macroscopic(homogenized) properties based on the microstructure of porous ceramics. In spite of the complexity of the random microstructure, the error between the predicted and the measured values was only 1%. Next, two applications to the process simulation of fiber reinforced polymer matrix composites are presented. The permeability characteristics are evaluated for sheared weave fabrics for resin transfer molding(RTM) simulation, and the thermoforming of FRTP sheet is analyzed considering the large deformation of the knit structure during the deep-draw forming was verified by comparison with the experimental results.

An Improved Multi-resolution image fusion framework using image enhancement technique

  • Jhee, Hojin;Jang, Chulhee;Jin, Sanghun;Hong, Yonghee
    • 한국컴퓨터정보학회논문지
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    • 제22권12호
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    • pp.69-77
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    • 2017
  • This paper represents a novel framework for multi-scale image fusion. Multi-scale Kalman Smoothing (MKS) algorithm with quad-tree structure can provide a powerful multi-resolution image fusion scheme by employing Markov property. In general, such approach provides outstanding image fusion performance in terms of accuracy and efficiency, however, quad-tree based method is often limited to be applied in certain applications due to its stair-like covariance structure, resulting in unrealistic blocky artifacts at the fusion result where finest scale data are void or missed. To mitigate this structural artifact, in this paper, a new scheme of multi-scale fusion framework is proposed. By employing Super Resolution (SR) technique on MKS algorithm, fine resolved measurement is generated and blended through the tree structure such that missed detail information at data missing region in fine scale image is properly inferred and the blocky artifact can be successfully suppressed at fusion result. Simulation results show that the proposed method provides significantly improved fusion results in the senses of both Root Mean Square Error (RMSE) performance and visual improvement over conventional MKS algorithm.

Low Resolution Rate Face Recognition Based on Multi-scale CNN

  • Wang, Ji-Yuan;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제21권12호
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    • pp.1467-1472
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    • 2018
  • For the problem that the face image of surveillance video cannot be accurately identified due to the low resolution, this paper proposes a low resolution face recognition solution based on convolutional neural network model. Convolutional Neural Networks (CNN) model for multi-scale input The CNN model for multi-scale input is an improvement over the existing "two-step method" in which low-resolution images are up-sampled using a simple bi-cubic interpolation method. Then, the up sampled image and the high-resolution image are mixed as a model training sample. The CNN model learns the common feature space of the high- and low-resolution images, and then measures the feature similarity through the cosine distance. Finally, the recognition result is given. The experiments on the CMU PIE and Extended Yale B datasets show that the accuracy of the model is better than other comparison methods. Compared with the CMDA_BGE algorithm with the highest recognition rate, the accuracy rate is 2.5%~9.9%.

MULTI-SCALE MODELING AND ANALYSIS OF CONVECTIVE BOILING: TOWARDS THE PREDICTION OF CHF IN ROD BUNDLES

  • Niceno, B.;Sato, Y.;Badillo, A.;Andreani, M.
    • Nuclear Engineering and Technology
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    • 제42권6호
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    • pp.620-635
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    • 2010
  • In this paper we describe current activities on the project Multi-Scale Modeling and Analysis of convective boiling (MSMA), conducted jointly by the Paul Scherrer Institute (PSI) and the Swiss Nuclear Utilities (Swissnuclear). The long-term aim of the MSMA project is to formulate improved closure laws for Computational Fluid Dynamics (CFD) simulations for prediction of convective boiling and eventually of the Critical Heat Flux (CHF). As boiling is controlled by the competition of numerous phenomena at various length and time scales, a multi-scale approach is employed to tackle the problem at different scales. In the MSMA project, the scales on which we focus range from the CFD scale (macro-scale), bubble size scale (meso-scale), liquid micro-layer and triple interline scale (micro-scale), and molecular scale (nano-scale). The current focus of the project is on micro- and meso-scales modeling. The numerical framework comprises a highly efficient, parallel DNS solver, the PSI-BOIL code. The code has incorporated an Immersed Boundary Method (IBM) to tackle complex geometries. For simulation of meso-scales (bubbles), we use the Constrained Interpolation Profile method: Conservative Semi-Lagrangian $2^{nd}$ order (CIP-CSL2). The phase change is described either by applying conventional jump conditions at the interface, or by using the Phase Field (PF) approach. In this work, we present selected results for flows in complex geometry using the IBM, selected bubbly flow simulations using the CIP-CSL2 method and results for phase change using the PF approach. In the subsequent stage of the project, the importance of effects of nano-scale processes on the global boiling heat transfer will be evaluated. To validate the models, more experimental information will be needed in the future, so it is expected that the MSMA project will become the seed for a long-term, combined theoretical and experimental program.

다척도 지붕에지 검출방법을 이용한 지문영상의 전처리에 대한 연구 (A Study On Preprocessing of Fingerprint Image Using Multi-Scale Roof Edges)

  • 김수겸
    • Journal of Advanced Marine Engineering and Technology
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    • 제29권2호
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    • pp.217-224
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    • 2005
  • A new roof edge detection method based on multi level scales of wavelet function is proposed in this paper roof edge and its direction are obtained in this new methods at one time. Besides. scale characteristics of detecting roof edge is analyzed. And a few new methods on fingerprint image pre-processing are described. A method segmenting foreground/background of fingerprint images is proposed, in which Prior estimation of direction field is not required any more. A segmentation method based on multi-scale roof edges is implemented. and the valid scale range of the method is defined. too. And the method is used to segment ridges and valleys in fingerprint images simultaneously The exact direction fields made up of the direction of each point in ridges can be obtained when detecting ridges exactly based on the roof edge detector, in comparison with the traditional coarse estimation of direction fields. Obviously. it will establish a solid foundation for the sequent fingerprint identification.