• Title/Summary/Keyword: adaptive search region

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A Study on Adaptive Moving Method of Search Region (탐색 영역의 적응적 이동에 관한 연구)

  • 김진태;이석호;최종수
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.8
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    • pp.129-136
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    • 1994
  • In this paper an adaptive moving method of the search region tracking the motion is proposed. The search region in BMA is determined by the capability of hardware implementation and the degree of motion. But once determined nothing can be changed during coding procedure. In this paper we predict the level of motion of the current block using motion vectors of previous frames without overhead information and change the location of the search region according to the level of the motion predicted. In short the proposed method can be archieved the dsirable effect such that the size of search region gets large when the motion is large. Results of experiments show that prediction efficiency has been improved by using adaptive moving method resulting in reduced prediction error in the blocks with large motion.

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Motion Estimation with Optical Flow-based Adaptive Search Region

  • Kim, Kyoung-Kyoo;Ban, Seong-Won;Won Sik cheong;Lee, Kuhn-Il
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.843-846
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    • 2000
  • An optical flow-based motion estimation algorithm is proposed for video coding. The algorithm uses block-matching motion estimation with an adaptive search region. The search region is computed from motion fields that are estimated based on the optical flow. The algorithm is based on the fact that true block-motion vectors have similar characteristics to optical flow vectors. Thereafter, the search region is computed using these optical flow vectors that include spatial relationships. In conventional block matching, the search region is fixed. In contrast, in the new method, the appropriate size and location of the search region are both decided by the proposed algorithm. The results obtained using test images show that the proposed algorithm can produce a significant improvement compared with previous block-matching algorithms.

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Fast Motion Estimation using Adaptive Search Region Prediction (적응적 탐색 영역 예측을 이용한 고속 움직임 추정)

  • Ryu, Kwon-Yeol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.7
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    • pp.1187-1192
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    • 2008
  • This paper proposes a fast motion estimation using an adaptive search region and a new three step search. The proposed method improved in the quality of motion compensation image as $0.43dB{\sim}2.19dB$, according as it predict motion of current block from motion vector of neigher blocks, and adaptively set up search region using predicted motion information. We show that the proposed method applied a new three step search pattern is able to fast motion estimation, according as it reduce computational complexity per blocks as $1.3%{\sim}1.9%$ than conventional method.

A Novel Region Decision Method with Mesh Adaptive Direct Search Applied to Optimal FEA-Based Design of Interior PM Generator

  • Lee, Dongsu;Son, Byung Kwan;Kim, Jong-Wook;Jung, Sang-Yong
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1549-1557
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    • 2018
  • Optimizing the design of large-scale electric machines based on nonlinear finite element analysis (FEA) requires longer computation time than other applications of FEA, mainly due to the huge size of the machines. This paper addresses a new region decision method (RDM) with mesh adaptive direct search (MADS) for the optimal design of wind generators in order to reduce the computation time. The validity of the proposed algorithm is evaluated using Rastrigin and Goldstein-Price benchmark function. Moreover, the algorithm is employed for the optimal design of a 5.6MW interior permanent magnet synchronous generator to minimize the torque ripple. Additionally, mechanical stress analysis as well as electromagnetic field analysis have been implemented to prevent breakdown caused by large centrifugal forces of the modified design.

The Image Segmentation Method using Adaptive Watershed Algorithm for Region Boundary Preservation

  • Kwon, Dong-Jin
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.1
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    • pp.39-46
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    • 2019
  • This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

An Adaptive Motion Estimation Technique Using Temporal Continuity of Motion

  • Park, Jung-Hyun;Lee, Kyeong-Hwan;Kim, Duk-Gyoo
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.7-10
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    • 2000
  • Fast block motion estimation technique is proposed to reduce the computational complexity in video coding. In the conventional methods the size of search region is fixed. For small motion regions like background the small size of sea of search region is enough to find a block motion. But for active motion regions the large size of search region is preferred to figure out the accurate motion vector. Therefore, it is reasonable that a block motion is estimated in the variable search region (both the size and the position of it). That is to say, the search region varies according to the predicted motion characteristics of a block. The block motion in video frames has temporal continuity and then the search region of a current block is predicted using the block motion of previous blocks. The computational complexity of the proposed technique is significantly reduced with a good picture quality compared to the conventional methods.

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Adaptive Learning Control of Electro-Hydraulic Servo System Using Real-Time Evolving Neural Network Algorithm (실시간 진화 신경망 알고리즘을 이용한 전기.유압 서보 시스템의 적응 학습제어)

  • Jang, Seong-Uk;Lee, Jin-Geol
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.7
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    • pp.584-588
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    • 2002
  • The real-time characteristic of the adaptive leaning control algorithms is validated based on the applied results of the hydraulic servo system that has very strong a non-linearity. The evolutionary strategy automatically adjusts the search regions with natural competition among many individuals. The error that is generated from the dynamic system is applied to the mutation equation. Competitive individuals are reduced with automatic adjustments of the search region in accordance with the error. In this paper, the individual parents and offspring can be reduced in order to apply evolutionary algorithms in real-time. The feasibility of the newly proposed algorithm was demonstrated through the real-time test.

Evolutionary Computation for the Real-Time Adaptive Learning Control(II) (실시간 적응 학습 제어를 위한 진화연산(II))

  • Chang, Sung-Ouk;Lee, Jin-Kul
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.730-734
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    • 2001
  • In this study in order to confirm the algorithms that are suggested from paper (I) as the experimental result, as the applied results of the hydraulic servo system are very strong a non-linearity of the fluid in the computer simulation, the real-time adaptive learning control algorithms is validated. The evolutionary strategy has characteristics that are automatically. adjusted in search regions with natural competition among many individuals. The error that is generated from the dynamic system is applied to the mutation equation. Competitive individuals are reduced with automatic adjustments of the search region in accord with the error. In this paper, the individual parents and offspring can be reduced in order to apply evolutionary algorithms in real-time as the description of the paper (I). The possibility of a new approaching algorithm that is suggested from the computer simulation of the paper (I) would be proved as the verification of a real-time test and the consideration its influence from the actual experiment.

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Adaptive Motion Estimation Algorithm UsingTemporal Continuity of Motion (움직임의 시간적 연속성을 이용한 적응적 움직임 추정 알고리즘)

  • Choi, Jung-Hyun;Lee, Kyeong-Hwan
    • Journal of Korea Multimedia Society
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    • v.7 no.8
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    • pp.1025-1034
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    • 2004
  • This paper proposes an adaptive motion estimation algorithm using the temporal continuity of motion. We set up a squared global search region (GSR), which basically corresponds to the search region of FSA, and non-squared adaptive local search regions (LSRs), the positions for which are predicted by the motion vectors of the temporal neighbor blocks, are constructed in the GSR. The previous frame blocks that possibly have effects on the current block are to be the temporal neighbor blocks. Because motion estimation is only performed in the areas made by LSRs, we can estimate motion more correctly and reduce processing time. Experimental results show that the proposed method can enhance visual qualities with significant reductions of complexity by reducing search regions, when compared to the conventional methods.

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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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