• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.174-177
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• 1995

Detecting a small threat object either fast moving or floating on shallow water presents a formidable challenge to shipboard sensor systems, which must determine whether or not to launch defensive weapons in a timely manner. An integrated multisensor concept is envisioned wherein the combined use of active and passive sensor is employed for the detection of short duration targets in dense ocean surface clutter to maximize detection range. The objective is to develop multisensor integration techniques that operate on detection data prior to track formation while simultaneously fusing contacts to tracks. In the system concept, detections from a low grazing angle search radar render designations to a sensor-search infrared sensor for target classification which in turn designates an active electro-optical sensor for sector search and target verification.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.39-45
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• 2010

In this paper we propose a new fast peak searching method using the gradient and present simulation results. The proposed method is a solution to the problem that finds the peak(maximum) of the unimodal function on a finite interval with minimum searching steps. Its main application is the auto-focus in the mobile phone. We propose the three steps to find the peak; periodic search, gradient-based search and detail search. In simulation we generated the Gaussian functions with white noise and have the result of about 8 searching steps and 1.04 errors on average.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.419-420
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• 2006

In the new video coding standard H.264/AVC, motion estimation (ME) is allowed to search multiple reference frames for improve the rate-distortion performance. The complexity of multi-frame motion estimation increases linearly with the number of used reference frame. However, the distortion gain given by each reference frame varies with the video sequence, and it is not efficient to search through all the candidate frames. In this paper, we propose a fast mult-frame selection method using all zero coefficient block (AZCB) prediction and sum of difference (SAD) of neighbor block. Simulation results show that the speed of the proposed algorithm is up to two times faster than exhaustive search of multiple reference frames with similar quality and bit-rate.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.430-435
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• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8455-8461
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• 2015

In this paper, we propose new search algorithms using SVD(Singular Value Decomposition) for fast search of Raman spectrum. In the proposed algorithms, small number of the eigen vectors obtained by SVD are chosen in accordance with their respective significance to achieve computation reduction. By introducing pilot test, we exclude large number of data from search and then, we apply partial distance search(PDS) for further computation reduction. We prepared 14,032 kinds of chemical Raman spectrum as the library for comparisons. Experiments were carried out with 7 methods, that is Full Search, PDS, 1DMPS modified MPS for applying to 1-dimensional space data with PDS(1DMPS+PDS), 1DMPS with PDS by using descending sorted variance of data(1DMPS Sort with Variance+PDS), 250-dimensional components of the SVD with PDS(250SVD+PDS) and proposed algorithms, PSP and PSSP. For exact comparison of computations, we compared the number of multiplications and additions required for each method. According to the experiments, PSSP algorithm shows 64.8% computation reduction when compared with 250SVD+PDS while PSP shows 157% computation reduction.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.389-391
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• 1999

영상 압축 기법에는 여러 가지 알고리즘을 적용되고 있다. 이런 알고리즘들에는 주파수 영역 중복을 제거하기 위한 DCT, 시간 중복성 제거를 위한 움직임 측정, 압축기법에 의해서 만들어진 정보를 부호화하는 VLC들이 있다. 이런 부호화 알고리즘들은 부호화기를 구현하는데 많은 시간을 요구하며 특히 움직임 추정은 부호화기의 절반에 가까운 시간을 소비한다. 움직임 측정 기술의 복잡도는 search algorithm, cost function, search range parameter의 요인으로 나타낼 수 있다. 본 논문에서는 기존의 Full Search 알고리즘 대신에 three-step 알고리즘을 사용하여 움직임 측정 시간을 줄였다. Full Search 알고리즘은 search area에서 모든 지역에 대해 cost function을 사용하여 이전 블록과 얼마나 유사한지를 조사한다. 따라서 이전 블록과 가장 유사한 부분을 찾는 좋은 방법이지만 그만큼 시간이 많이 사용한다. Three-step 알고리즘은 search area의 일정 지역에 대해 cost function를 사용하여 이전 블록과의 유사성을 찾는 fast 알고리즘이다. Three-step 알고리즘을 사용한 경우 기존의 full search 알고리즘을 사용할 때 보다 60% 정도의 시간이 단축되었다. 그리고 생성되는 압축 데이터의 크기는 full search 알고리즘을 사용할 때 보다 많이 차지한다. 생성되는 H.263파일의 화질에서는 Three-step 알고리즘을 사용한 경우일지라도 full search 알고리즘을 사용한 경우와 거의 비슷한 화질을 보여준다.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.43-45
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• 2000

For motion estimation, the block matching algorithm is widely used to improve the compression ratio of low bit-rate motion video. As a newly developed fast search algorithm, the nearest-neighbors search technique has a drawback of degrading video quality while providing fisher speed in search process. In this paper, a modified nearest-neighbors search algorithm is proposed in which a double rectangular shaped search-candidate area is used to improve video quality in encoding process with a small increasing of search time. To evaluate the proposed algorithm. other methods based on the nearest-neighbors search algorithm are investigated.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.86-94
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• 1998

This paper proposes a new fast block-matching algorithm, named MFSS(Modified Four-Step Search) algorithm, which has better performance and is more adequate for hardware realization than the existing fast algorithms. The proposed algorithm is suitable for hardware realization since it has a unique regularity during the search procedure. It is shown from simulation results that its performance is close to that of FS(Full Search) algorithm. This paper also proposes a VLSI architecture and presents some design results of a motion estimator and compensator which adopted the MFSS algorithm. The important aspects considered in designing a motion estimator and compensator are hardware complexity of design results, and total delay needed to generate the motion compensated data after finding the motion vectors. Hardware complexity is minimized by using just nine PE(Process Element)'s, and total delay is minimized by sharing search memory of the motion estimator and compensator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1232-1239
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• 2006

In video standards such as MPEG-1/2/4 and H.264/AVC, motion estimation / compensation(ME/MC) process causes the most encoding complexity of video encoder. The full search method, which is used in general video codecs, exhausts much encoding time because it compares current macroblock with those at all positions within search window for searching a matched block. For the alleviation of this problem, the fast search methods such as TSS, NTSS, DS and HEXBS are exploited at first. Thereafter, DS based MVFAST, PMVFAST, MAS and FAME, which utilize temporal or spacial correlation characteristics of motion vectors, are developed. But there remain the problems of image quality degradation and algorithm complexity increase. In this thesis, the proposed algorithm maximizes search speed and minimizes the degradation of image quality by determining initial search point correctly and using simple one-dimension search patterns considering motion characteristics of each frame.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.79-85
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• 2010

In video standards such as H.264/AVC, motion estimation (ME) / compensation (MC) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. The full search technique, which is used in general video codecs, gives the highest visual quality but also has the problem of significant computational load. To solve this problem, many fast algorithm has benn proposed. Among them, NPDS show that can maintain its video quality very close to the full search technique while achieving computation reduction by using a halfway-stop technique in the calculation of block distortion measure. In this paper, we proposed algorithm by determining minimum distortion measure with predictive motion vector and using the new search order. As the result, we can check that the proposed algorithm reduces the computational load 95% in average compared to the full search, respectively with the PSNR lost about 0.04dB.