• Title/Summary/Keyword: hierarchical matching

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A QRS Pattern Analysis Algorithm for ECG Signals (심전도신호의 QRS 패턴해석)

  • 황선철;권혁제
    • Journal of Biomedical Engineering Research
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    • v.12 no.2
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    • pp.131-138
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    • 1991
  • This paper describes an algorithm of pattern analysis of ECG signals by significant points extraction method. The significant points can be extracted by modified zerocrossing method, which method determines the real significant point among the significant point candidates by zerocrossing method and slope rate of left side and right side. This modified zerocrossing method improves the accuracy of detection of real slgnficant polnt Position. This Paper also describes the pattern matching algorithm by a hierarchical AND/OR graph of ECG signals. The decomposition of ECG signals by a hierarchical AND/ OR graph can make the pattern matching process easy and fast, Furthermore the pattern matching to the significant points reduces the processing time of ECG analysis.

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A Fast Block Matching Algorithm Using Hierarchical Search Point Sampling (계층적인 탐색점 추출을 이용한 고속 블록 정합 알고리즘)

  • 정수목
    • Journal of the Korea Computer Industry Society
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    • v.4 no.12
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    • pp.1043-1052
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    • 2003
  • In this paper, we present a fast motion estimation algorithm to reduce the computations of block matching algorithm for motion estimation in video coding. The proposed algorithm is based on Multi-level Successive Elimination Algorithm and Efficient Multi-level Successive Elimination Algorithms. The best estimate of the motion vectors can be obtained by hierarchical search point sampling and thus the proposed algorithm can decrease the number of matching evaluations that require very intensive computations. The efficiency of the proposed algorithm was verified by experimental results.

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STATISTICAL NOISE BAND REMOVAL FOR SURFACE CLUSTERING OF HYPERSPECTRAL DATA

  • Huan, Nguyen Van;Kim, Hak-Il
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.111-114
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    • 2008
  • The existence of noise bands may deform the typical shape of the spectrum, making the accuracy of clustering degraded. This paper proposes a statistical approach to remove noise bands in hyperspectral data using the correlation coefficient of bands as an indicator. Considering each band as a random variable, two adjacent signal bands in hyperspectral data are highly correlative. On the contrary, existence of a noise band will produce a low correlation. For clustering, the unsupervised ${\kappa}$-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID. Furthermore, this paper proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures.

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Bayesian Estimation Using Noninformative Priors in Hierarchical Model

  • Kim, Dal-Ho;Choi, Jin-Kap;Choi, Hee-Jo
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.1033-1043
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    • 2004
  • We consider the simultaneous Bayesian estimation for the normal means based on different noninformative type hyperpriors in hierarchical model. We provide numerical example using the famous baseball data in Efron and Morris (1975) for illustration.

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Artificial Neural Network-based Weight Factor Determination Method for the Enhanced XML Schema Matching of Bridge Engineering Documents (교량 건설 문서의 강화된 XML 스키마 매칭을 위한 인공신경망 기반의 요소 가중치 선정 방안)

  • Park, Sang I.;Kwon, Tae-Ho;Park, Junwon;Seo, Kyung-Wan;Yoon, Young-Cheol
    • Journal of the Korean Society of Safety
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    • v.37 no.1
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    • pp.41-48
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    • 2022
  • Bridge engineering documents have essential contents that must be referenced continuously throughout a structure's entire life cycle, but research related to the quality of the contents is still lacking. XML schema matching is an excellent technique to improve the quality of stored data; however, it takes excessive computing time when applied to documents with many contents and a deep hierarchical structure, such as bridge engineering documents. Moreover, it requires a manual parametric study for matching elements' weight factors, maintaining a high matching accuracy. This study proposes an efficient weight-factor determination method based on an artificial neural network (ANN) model using the simplified XML schema-matching method proposed in a previous research to reduce the computing time. The ANN model was generated and verified using 580 data of document properties, weight factors, and matching accuracy. The proposed ANN-based schema-matching method showed superiority in terms of accuracy and efficiency compared with the previous study on XML schema matching for bridge engineering documents.

Toward Occlusion-Free Depth Estimation for Video Production

  • Park, Jong-Il;Seiki-Inoue
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1997.06a
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    • pp.131-136
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    • 1997
  • We present a method to estimate a dense and sharp depth map using multiple cameras for the application to flexible video production. A key issue for obtaining sharp depth map is how to overcome the harmful influence of occlusion. Thus, we first propose to selectively use the depth information from multiple cameras. With a simple sort and discard technique, we resolve the occlusion problem considerably at a slight sacrifice of noise tolerance. However, boundary overreach of more textured area to less textured area at object boundaries still remains to be solved. We observed that the amount of boundary overreach is less than half the size of the matching window and, unlike usual stereo matching, the boundary overreach with the proposed occlusion-overcoming method shows very abrupt transition. Based on these observations, we propose a hierarchical estimation scheme that attempts to reduce boundary overreach such that edges of the depth map coincide with object boundaries on the one hand, and to reduce noisy estimates due to insufficient size of matching window on the other hand. We show the hierarchical method can produce a sharp depth map for a variety of images.

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A Hierarchical Stereo Matching Algorithm Using Wavelet Representation (웨이브릿 변환을 이용한 계층적 스테레오 정합)

  • 김영석;이준재;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.8
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    • pp.74-86
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    • 1994
  • In this paper a hierarchical stereo matching algorithm to obtain the disparity in wavelet transformed domain by using locally adaptive window and weights is proposed. The pyramidal structure obtained by wavelet transform is used to solve the loss of information which the conventional Gaussian or Laplacian pyramid have. The wavelet transformed images are decomposed into the blurred image the horizontal edges the vertical edges and the diagonal edges. The similarity between each wavelet channel of left and right image determines the relative importance of each primitive and make the algorithm perform the area-based and feature-based matching adaptively. The wavelet transform can extract the features that have the dense resolution as well as can avoid the duplication or loss of information. Meanwhile the variable window that needs to obtain precise and stable estimation of correspondense is decided adaptively from the disparities estimated in coarse resolution and LL(low-low) channel of wavelet transformed stereo image. Also a new relaxation algorithm that can reduce the false match without the blurring of the disparity edge is proposed. The experimental results for various images show that the proposed algorithm has good perfpormance even if the images used in experiments have the unfavorable conditions.

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A Persistent Naming of Shells

  • Marcheix, David
    • International Journal of CAD/CAM
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    • v.6 no.1
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    • pp.125-137
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    • 2006
  • Nowadays, many commercial CAD systems support history-based, constraint-based and feature-based modeling. Unfortunately, most systems fail during the re-evaluation phase when various kind of topological changes occur. This issue is known as "persistent naming" which refers to the problem of identifying entities in an initial parametric model and matching them in the re-evaluated model. Most works in this domain focus on the persistent naming of atomic entities such as vertices, edges or faces. But very few of them consider the persistent naming of aggregates like shells (any set of faces). We propose in this paper a complete framework for identifying and matching any kind of entities based on their underlying topology, and particularly shells. The identifying method is based on the invariant structure of each class of form features (a hierarchical structure of shells) and on its topological evolution (an historical structure of faces). The matching method compares the initial and the re-evaluated topological histories, and computes two measures of topological similarity between any couple of entities occurring in both models. The naming and matching method has been implemented and integrated in a prototype of commercial CAD Software (Topsolid).

A Hierarchical Block Matching Algorithm Based on Camera Panning Compensation (카메라 패닝 보상에 기반한 계층적 블록 정합 알고리즘)

  • Gwak, No-Yun;Hwang, Byeong-Won
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.8
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    • pp.2271-2280
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    • 1999
  • In this paper, a variable motion estimation scheme based on HBMA(Hierarchical Block Matching Algorithm) to improve the performance and to reduce heavy computational and transmission load, is presented. The proposed algorithm is composed of four steps. First, block activity for each block is defined using the edge information of differential image between two sequential images, and then average block activity of the present image is found by taking the mean of block activity. Secondly, camera pan compensation is carried out, according to the average activity of the image, in the hierarchical pyramid structure constructed by wavelet transform. Next, the LUT classifying each block into one among Moving, No Moving, Semi-Moving Block according to the block activity compensated camera pan is obtained. Finally, as varying the block size and adaptively selecting the initial search layer and the search range referring to LUT, the proposed variable HBMA can effectively carries out fast motion estimation in the hierarchical pyramid structure. The cost function needed above-mentioned each step is only the block activity defined by the edge information of the differential image in the sequential images.

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Hierarchical Search-based Fast Schemes for Consecutive Block Error Concealment (연속된 블록 오류 은닉을 위한 계층 탐색 기반의 고속 알고리즘)

  • Jeon Soo-Yeol;Sohn Chae-Bong;Oh Seoung-Jun;Ahn Chang-Beom
    • Journal of Broadcast Engineering
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    • v.9 no.4 s.25
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    • pp.446-454
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    • 2004
  • With the growth of multimedia systems, compressing image data has become more important in the area of multimedia services. Since a compressed image bitstream can often be seriously distorted by various types of channel noise, an error concealment algorithm becomes a very important issue. In order to solve this problem, Hsia proposed the error concealment algorithm where he recovered lost block data using 1D boundary matching vectors. His algorithm, however, requires high computational complexity since each matching vector needs MAD (Mean Absolute Difference) values of all pixels, which is either a boundary line top or a boundary line bottom of a damaged block. We propose a hierarchical search-based fast error concealment scheme as well as its approximated version to reduce computational time. In the proposed scheme, a hierarchical search is applied to reduce the number of checking points for searching a vector. The error concealment schemes proposed in this paper can be about 3 times faster than Hsia's with keeping visual quality and PSNR.