• Title/Summary/Keyword: Image-Based Simulation

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Investigation of Strain Measurements using Digital Image Correlation with a Finite Element Method

  • Zhao, Jian;Zhao, Dong
    • Journal of the Optical Society of Korea
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    • v.17 no.5
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    • pp.399-404
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    • 2013
  • This article proposes a digital image correlation (DIC) strain measurement method based on a finite element (FE) algorithm. A two-step digital image correlation is presented. In the first step, the gradient-based subpixels technique is used to search the displacements of a region of interest of the specimen, and then the strain fields are obtained by utilizing the finite element method in the second step. Both simulation and experiment processing, including tensile strain deformation, show that the proposed method can achieve nearly the same accuracy as the cubic spline interpolation method in most cases and higher accuracy in some cases, such as the simulations of uniaxial tension with and without noise. The results show that it also has a good noise-robustness. Finally, this method is used in the uniaxial tensile testing for Dahurian Larch wood specimens with or without a hole, and the obtained strain values are close to the results which were obtained from the strain gauge and the cubic spline interpolation method.

A Wavelet Transform based Watermarking for Digital Signatures

  • Oh, Sang-Heun;Lee, Hee-Sup;Lee, Keun-Young
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.857-860
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    • 2000
  • This paper presents a new watermarking method based on wavelet transform. Embedding algorithm call define robust area by varying thresholds and gives a watermark image the priority of significance by analyzing spatial correlation of the watermark image. Detector can adjust thresholds to the distorted watermarked image. Also detector can extract the embedded data without an original image. A new measurement for detecting the correct watermark is suggested. Simulation results show that the embedded watermark is robust against various signal processing and compression attacks.

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Moving image coding with variablesize block based on the segmentation of motion vectors (움직임 벡터의 영역화에 의한 가변 블럭 동영상 부호화)

  • 김진태;최종수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.3
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    • pp.469-480
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    • 1997
  • For moving image coding, the variable size of region coding based on local motion is more efficient than fixed size of region coding. It can be applied well to complex motions and is more stable for wide motions because images are segmented according to local motions. In this paper, new image coding method using the segmentation of motion vectors is proposed. First, motion vector field is smoothed by filtering and segmented by smoothed motion vectors. The region growing method is used for decomposition of regions, and merging of regions is decided by motion vector and prediction errors of the region. Edge of regions is excluded because of the correlation of image, and neighbor motion vectors are used evaluation of current block and construction of region. The results of computer simulation show the proposed method is superior than the existing methods in aspect of coding efficiency.

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The Improved Watershed Algorithm using Adaptive Local Threshold (적응적 지역 임계치를 이용한 개선된 워터쉐드 알고리즘)

  • Lee Seok-Hee;Kwon Dong-Jin;Kwak Nae-Joung;Ahn Jae-Hyeong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.11a
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    • pp.891-894
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    • 2004
  • This paper proposes an improved image segmentation algorithm by the watershed algorithm based on the local adaptive threshold on local minima search and the fixing threshold on label allocation. The previous watershed algorithm generates the problem of over-segmentation. The over-segmentation makes the boundary in the inaccuracy region by occurring around the object. In order to solve those problems we quantize the input color image by the vector quantization, remove noise and find the gradient image. We sorted local minima applying the local adaptive threshold on local minima search of the input color image. The simulation results show that the proposed algorithm controls over-segmentation and makes the fine boundary around segmented region applying the fixing threshold based on sorted local minima on label allocation.

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Edge Detection Method Based on Neural Networks for COMS MI Images

  • Lee, Jin-Ho;Park, Eun-Bin;Woo, Sun-Hee
    • Journal of Astronomy and Space Sciences
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    • v.33 no.4
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    • pp.313-318
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    • 2016
  • Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

An Accurate Design Method of Wideband BPF Considering Frequency Dependence of Inverters

  • Youna, Jang;Dal, Ahn
    • Journal of information and communication convergence engineering
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    • v.21 no.1
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    • pp.1-8
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    • 2023
  • This paper presents a design method for a wideband bandpass filter (BPF) which compensates for frequency dependency based on the image admittance and image phase. In the proposed method, new compensation methods for the admittance and phase are integrated with the conventional method. The proposed method improves the frequency shift and reduces the unwanted bandwidth when designing more than 20% of the Fractional Bandwidth (FBW), whereas the conventional method exhibits frequency degradation at only 10% FBW. The proposed design theory was verified by applying it to both lumped elements and distributed lines through circuit simulation and measurements without an optimization process. The measurement results demonstrate improvements in the frequency shift and target bandwidth. In the future, an accurate design method based on frequency dependence can be implemented for the next-generation broadband communication system applications.

The software configuration management system for image processing algorithm development (영상처리 알고리즘 개발을 위한 소프트웨어형상관리시스템)

  • Lee Jeong-Heon;Chae Ok-Sam
    • The KIPS Transactions:PartB
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    • v.12B no.1 s.97
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    • pp.1-8
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    • 2005
  • The importance of software is getting high in development of the digital device (digital camcoder, digital camera, mp3 player, ....). And because the sire of software becomes larger and complicated, the necessity of software configuration management (to solves a software crisis) is increased. The general software configuration management system shows lack of the property and features of software development environment for image processing algorithm due to its wide range to be covered. Image processing algorithm development environment has properties like repetitive analysis and simulation using visual programming environment where, beside support of elementary development functions. component(or library) can be combined and tested interactively. Moreover, the method to look fast and effectively for component having similar function is required. In this paper, we present the system which supports the software configuration management method for a simulation tool and the property in the visual programming environment. And we relate our system to real simulation tool so as to check its ability as the software configuration management system for image processing algorithm development environment.

A Mixed Nonlinear Filter for Image Restoration under AWGN and Impulse Noise Environment

  • Gao, Yinyu;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • v.9 no.5
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    • pp.591-596
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    • 2011
  • Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which is called mixed noise and it produces a hard damage. In this paper, we proposed noise type classification method and a mixed nonlinear filter for mixed noise suppression. The proposed filtering scheme applies a modified adaptive switching median filter to impulse noise suppression and an efficient nonlinear filer was carried out to remove Gaussian noise. The simulation results based on Matlab show that the proposed method can remove mixed Gaussian and impulse noise efficiently and it can preserve the integrity of edge and keep the detailed information.

The Parameter Learning Method for Similar Image Rating Using Pulse Coupled Neural Network

  • Matsushima, Hiroki;Kurokawa, Hiroaki
    • Journal of Multimedia Information System
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    • v.3 no.4
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    • pp.155-160
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    • 2016
  • The Pulse Coupled Neural Network (PCNN) is a kind of neural network models that consists of spiking neurons and local connections. The PCNN was originally proposed as a model that can reproduce the synchronous phenomena of the neurons in the cat visual cortex. Recently, the PCNN has been applied to the various image processing applications, e.g., image segmentation, edge detection, pattern recognition, and so on. The method for the image matching using the PCNN had been proposed as one of the valuable applications of the PCNN. In this method, the Genetic Algorithm is applied to the PCNN parameter learning for the image matching. In this study, we propose the method of the similar image rating using the PCNN. In our method, the Genetic Algorithm based method is applied to the parameter learning of the PCNN. We show the performance of our method by simulations. From the simulation results, we evaluate the efficiency and the general versatility of our parameter learning method.

Application of PRA to The Differenec Image for Prediction Error Reduction in DPCM Image Coding (DPCM 영상 부호화기에서 예측 오차를 줄이기 위한 변환된 영상에서의 PRA 적용)

  • 문주희;고종석;김재균
    • Proceedings of the Korean Institute of Communication Sciences Conference
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    • 1986.10a
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    • pp.56-58
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    • 1986
  • This paper propose a conversion method to reduce prediction error produced when PRA(Pel Recursive Algorithm) motion estimation method is used in real image. The method is th get a spatial difference image from a given raw image and then to apply any PRA method to the difference image. The algorithm proposed in this paper is compared with several algorithm including the ubiquitious Netravali and Robbins` based on the performance and the hardware complexity. Computer simulation shows that the difference image conversion method is about 4.5dB better than the other algorithm with regard to prediction error power.

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