• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.959-968
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• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.13-20
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• 2003

Based on the studies on the motion vector distributions estimated on the image sequences, we proposed constrained diamond search (DS) algorithm for fast block-matching motion estimation. By considering the fact that motion vectors are searched within the 2 pixels distance in vertically and horizontally on average, we confirmed that DS algorithm achieves close performance on error ratio and requires less computation compared with new three-step search (NTSS) algorithm. Also, by applying displaced frame difference (DFD) to DS algorithm, we reduced the computational loads needed to estimate the motion vectors within the stable block that do not have motions. And we reduced the possibilities falling into the local minima in the course of estimation of motion vectors by applying DFD to DS algorithm. So, we knew that proposed constrained DS algorithm achieved enhanced results as aspects of error ratio and the number of search points to be necessary compared with conventional DS algorithm, four step search (FSS) algorithm, and block-based gradient-descent search algorithm

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.515-522
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• 2001

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Map(SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data, and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. We implemented about k-NN search for similar image classification as to (1) access to topological feature map, and (2) apply to pruning strategy of high speed search. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.129-133
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• 2015

In this paper, we propose a fast motion estimation algorithm which is important in the performance of video encoding. Conventional fast motion estimation algorithms have serious problems of low prediction quality in some frames and still much computation. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution of probability of motion vectors, divides search range into several groups according to its importance, and applies adaptive block matching criteria for each group of search range. The proposed algorithm takes only 3~5% in computational amount and has decreased prediction quality about 0~0.01dB compared with the fast full search algorithm.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1928-1931
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• 2003

본 논문은 가장 최근의 동영상 국제표준인 H.264 비디오 코덱을 사용하여 QCIF 영상을 초당 10 프레임 정도의 속도로 실시간 부호화하는 것을 목적으로, 부호화 시 필요한 연산의 약 80％-90％를 차지하는 움직임 추정을 고속으로 처리할 수 있는 알고리즘을 개발하는 것을 내용으로 하고 있다. 제안하는 고속 움직임 추정 알고리즘은 MPEG겨 등의 고속 움직임 추정에 사용되었던 기존의 알고리즘을 다중 프레임 레퍼런스 등 새로운 특징을 갖는 H.264 코덱에 적합한 형태로 개선하고, 움직임 추정의 정밀도가 1/4 화소 단위로 향상됨으로써 늘어난 부화소단위 움직임 추정의 상대적 부담을 함께 고려하면서, 모드 선택과정과 효과적으로 결합함으로써 보다 향상된 성능을 나타내고 있다. 모의실험 결과, 기존의 공식 JVT-AVC 레퍼런스 소프트웨어인 JM (Joint Model) 에 구현되어 있는 고속 움직임 추정 알고리즘에 비해서 최대 80％, 평균적으로 60％의 속도개선 효과가 있음이 입증되어, 최근 JM 의 새로운 고속 움직임 추정 알고리즘으로 채택된 JVT-F0l7 알고리즘에 본 논문에서 제안하는 레퍼런스 프레임 탐색 제한 알고리즘을 결합시킴으로써 추가적으로 약 45％의 속도 개선을 얻을 수 있음을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.54-63
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• 2000

We present a multi-resolution block matching algorithm (BMA) for fast motion estimation At the coarsest level, a motion vector (MV) having minimum matching error is chosen via a full search, and a MV with minimum matching error is concurrently found among the MVs of the spatially adjacent blocks Here, to examine the spatial MVs accurately, we propose an efficient method for searching full resolution MV s without MV quantization even at the coarsest level The chosen two MV s are used as the initial search centers at the middle level At the middle level, the local search is performed within much smaller search area around each search center If the method used at the coarsest level is adopted here, the local searches can be done at integer-pel accuracy A MV having minimum matching error is selected within the local search areas, and then the final level search is performed around this initial search center Since the local searches are performed at integer-pel accuracy at the middle level, the local search at the finest level does not take an effect on the overall performance So we can skip the final level search without performance degradation, thereby the search speed increases Simulation results show that in comparison with full search BMA, the proposed BMA without the final level search achieves a speed-up factor over 200 with minor PSNR degradation of 02dB at most, under a normal MPEG2 coding environment Furthermore, our scheme IS also suitable for hardware implementation due to regular data-flow.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.78-84
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• 2009

In general video coding systems, motion estimation (ME) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. Fractional pixel motion estimation can improve the video compression rate at the cost of higher computational complexity. It is based on the experimental results that the sum of absolute differences (SAD) shows parabolic shape and thus can be approximated by using interpolation technique. In this paper, we propose a fast fractional pixel search algorithm by combining SASR (Simplified Adaptive Search Range) and the CBCDS (Center Biased Cross-Diamond Search) pattern with the predicted motion vector. Compare with the fractional pel full search and the CBFPS, the proposed CBCDS algorithms can reduce fractional pel search points up to 81.4%, respectively with the PSNR lost about 0.05dB.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.85-91
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• 2013

This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.

• Aerospace Engineering and Technology
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• v.6 no.1
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• pp.6-13
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• 2007

PAV(Personal Air Vehicle) can be an alternative of the saturated ground transportation in future and can be available in any time and anywhere. This paper describes some overview on high speed rotorcraft concepts for the PAV applications. First the requirement of PAV is surveyed. Then the existing concepts of high speed rotorcrafts are reviewed. Several on-going projects are summarized. Finally! technical issues of high speed rotorcraft to apply to PAV platform are explored.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.483-491
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• 2009

In this paper, we propose a fast motion estimation algorithm using adaptive elimination of sub-block partial coefficients. The proposed algorithm predicts an adaptive threshold for each sub-block by using relationship of an initial sum of absolute difference(SAD) and a minimum SAD at the current point, and efficiently reduces unnecessary calculation time of the conventional partial distortion elimination(PDE) algorithm with the predicted threshold. Our algorithm reduces about 60% of computations of the conventional PDE algorithm without any degradation of prediction quality compared with the con ventional full search. Additionally, the proposed algorithm can be applied to other fast motion estimation 떠gorithms. the proposed Our proposing algorithm will be useful to real-time video coding applications using MPEG-2 or MPEG-4 AVC standards.