• Title/Summary/Keyword: matching algorithm

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A Past Elimination Algorithm of Impossible Candidate Vectors Using Matching Scan Method in Motion Estimation of Full Search (전영역 탐색 방식의 움직임 예측에서 매칭 스캔 방법을 이용한 불가능한 후보 벡터의 고속 제거 알고리즘)

  • Kim Jone-Nam
    • Journal of Korea Multimedia Society
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    • v.8 no.8
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    • pp.1080-1087
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    • 2005
  • Significant computations for full search (FS) motion estimation have been a big obstacle in real-time video coding and recent MPEG-4 AVC (advanced video coding) standard requires much more computations than conventional MPEG-2 for motion estimation. To reduce an amount of computation of full search (FS) algorithm for fast motion estimation, we propose a new and fast matching algorithm without any degradation of predicted images like the conventional FS. The computational reduction without any degradation in predicted image comes from fast elimination of impossible candidate motion vectors. We obtain faster elimination of inappropriate motion vectors using efficient matching units from localization of complex area in image data and dithering order based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination (PDE) algorithm, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

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Size-Variable Block Matching for Extracting Motion Information (동작정보 추출을 위한 가변적 탐색 영역과 블록 크기의 정합)

  • Jang, Seok;Kim, Bong-Keun;Kim, Gye-Young;Choi, Hyung-Il
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.321-328
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    • 2003
  • This Paper Proposes a size-variable block matching algorithm for motion vector extraction. The Proposed algorithm dynamically determines the search area and the size of a block. We exploit the constraint of small velocity changes of a block along the time to determine the origin of the search area. The range of the search area is adjusted according to the motion coherency of spatially neighboring blocks. The process of determining the sire of a block begins matching with a small block. If the matching degree is not good enough, we expand the size of a block a little bit and then repeat the matching process until our matching criterion Is satisfied. The experimental results show that the proposed algorithm can yield very accurate block motion vectors. Our algorithm outperforms other algorithms in terms of the estimated motion vectors, though our algorithm requires some computational overhead.

XML Element Matching Algorithm based on Structural Properties and Rules (룰과 구조적 속성에 기반한 XML 엘리먼트 매칭 알고리즘)

  • Park, Hyung;Jeong, Chanki
    • Journal of Information Technology and Architecture
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    • v.10 no.1
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    • pp.71-77
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    • 2013
  • XML schema matching is the task of finding semantic correspondences between elements of two schemas. XML schema matching plays an important role in many application, such as schema integration, data integration, data warehousing, data transformation, peer-to-peer data management, semantic web etc. In this paper, we propose an XML element matching algorithm based on rules and structural properties. The proposed algorithm involves classifying elements as unique or non-unique elements according to the structural properties of XML documents and deciding on element matching in accordance with rules. We present experimental results that demonstrate the effectiveness of the proposed approach.

Fast Motion Estimation Algorithm Using Limited Sub-blocks (제한된 서브블록을 이용한 고속 움직임 추정 알고리즘)

  • Kim Seong-Hee;Oh Jeong-Su
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.3C
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    • pp.258-263
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    • 2006
  • Each pixel in a matching block does not equally contribute to block matching and the matching error is greatly affected by image complexity. On the basis of the facts, this paper proposes a fast motion estimation algorithm using some sub-blocks selected by the image complexity. The proposed algorithm divides a matching block into 16 sub-blocks, computes the image complexity in every sub-block, executes partial block matching using some sub-blocks with large complexity, and detects a motion vector. The simulation results show that the proposed algorithm brings about negligible image degradation, but can reduce a large amount of computation in comparison with conventional algorithms.

Fine Granular Scalable Coding using Matching Pursuit with Multi-Step Search (다단계 탐색 기반 Matching Pursuit을 이용한 미세 계층적 부호화 기법)

  • 최웅일
    • Journal of Broadcast Engineering
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    • v.6 no.3
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    • pp.225-233
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    • 2001
  • Real-time video communication applications over Internet should be able to support such functionality as scalability because of the unpredictable and varying channel bandwidth between server and client. To accommodatethe wide variety of channel bitrates, a new scalable coding tool, namely the Fine Granular Scalability (FGS) coding tool has been reduce the adopted In the MPEG-4 video standard. This paper presentsa new FGS algorithm with matching Pursuit that can reduce the computational complexity of ordinal matching pursuit-based algorithm. The Proposed coding algorithm can make trade-off between Picture Quality and computationalcomplexity. Our simulation result shows that the proposed algorithm can reduce the computational cumplexity up to 1/5 compared to the conventional FGS method while retaining a similar picture quality.

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2D Grid Map Compensation Using ICP Algorithm based on Feature Points (특징 점 기반의 ICP 알고리즘을 이용한 2차원 격자지도 보정)

  • Hwang, Yu-Seop;Lee, Dong-Ju;Yu, Ho-Yun;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.10
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    • pp.965-971
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    • 2015
  • This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.

An Accurate Edge-Based Matching Using Subpixel Edges (서브픽셀 에지를 이용한 정밀한 에지기반 정합)

  • Cho, Tai-Hoon
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.5
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    • pp.493-498
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    • 2007
  • In this paper, a 2-dimensional accurate edge-based matching algorithm using subpixel edges is proposed that combines the Generalized Hough Transform(GHT) and the Chamfer matching to complement the weakness of either method. First, the GHT is used to find the approximate object positions and orientations, and then these positions and orientations are used as starting parameter values to find more accurate position and orientation using the Chamfer matching with distance interpolation. Finally, matching accuracy is further refined by using a subpixel algorithm. Testing results demonstrate that greater matching accuracy is achieved using subpixel edges rather than edge pixels.

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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Block Matching Motion Estimation Using Fast Search Algorithm (고속 탐색 알고리즘을 이용한 블록정합 움직임 추정)

  • 오태명
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.3
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    • pp.32-40
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    • 1999
  • In this paper, we present a fast block matching motion estimation algorithm based on successive elimination algorithm (SEA). Based on the characteristic of center-biased motion vector distribution in the search area, the proposed method improves the performance of the SEA with a reduced the number of the search positions in the search area, In addition, to reduce the computational load, this method is combined with both the reduced bits mean absolute difference (RBMAD) matching criterion which can be reduced the computation complexity of pixel comparison in the block matching and pixel decimation technique which reduce the number of pixels used in block matching. Simulation results show that the proposed method provides better performance than existing fast algorithms and similar to full-search block motion estimation algorithm.

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Template Matching-Based Target Recognition Algorithm Development and Verification using SAR Images (SAR 영상을 이용한 템플릿 매칭 기반 자동식별 알고리즘 구현 및 성능시험)

  • Lim, Ho;Chae, Daeyoung;Yoo, Ji Hee;Kwon, Kyung-Il
    • Journal of the Korea Institute of Military Science and Technology
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    • v.17 no.3
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    • pp.364-377
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    • 2014
  • In this paper, we have developed a target recognition algorithm based on a template matching technique using Synthetic Aperture Radar (SAR) images. For efficient computations, Radon transform-based azimuth estimation algorithm was used with the template matching. MSTAR data set was divided into two groups according to the depression angles, which were a train set and a test set. Template data were generated by rotating and cropping chips which were from MSTAR train set using the azimuth estimation algorithm. Then the template matching process between test data and template data was performed under various conditions. Performance variation according to contrast enhancement preprocessing which is scarce in open literature was also presented. The analysis results show that the target recognition algorithm could be useful for the automatic target recognition using SAR images.