• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1392-1400
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• 1999

In this paper, we propose a two-stage fast full search algorithm for block motion estimation that produces the same performance to that of full search algorithm (FSA) but with remarkable computation reduction. The proposed algorithm uses the search region subsampling and the difference of adjacent pixels in the current block. In the first stage, we subsample the search region by a factor of 9, and then calculate mean absolute error (MAE) at the subsampled search points. And in the second stage, we reduce the search points that need block matching process by using the lower bound of MAE value at each search Point. We Set the lower bound of MAE value for each search point from the MAE values which are calculated at the first stage and the difference of adjacent pixels in the current block. The experimental results show that we can reduce the computational complexity considerably without any degradation of picture quality.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.49-53
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• 2006

A fast motion-estimation algorithm based on regulated partial block distortions is proposed. The proposed algorithm can obtain very accurate motion vectors with a small computational load. Simulation results show that the proposed scheme provides very close performance to the full search while it is about 6 to 28 times faster than the full search.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11C
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• pp.1091-1097
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• 2005

In this paper, we propose fast motion estimation algorithm. Local statistics of a motion vector is highly correlated to motion vectors of its neighboring blocks. According to the property, block-based motion search range is adaptively determined in order to reduce unnecessary search points. Based on the determined search range, motion vector is obtained by variable step search motion estimation. Experimental results show that comparing to Full search motion estimation, the motion searching points of proposed algorithm is reduced as much as $98\%$. Moreover, PSNR and Bit Rate are almost same to Full search method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.313-325
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• 1996

This paper presents a new architecture for full-search block-matching motion estimation. The architecture is based on linear systolic arrays. High speed operation is obtained by feeding reference data, search data, and control signals into the linear systolic array in a pipelined fashion. Input data are fed into the linear systolic array at a half of the processor speed, reducing the required data bandwidth to half. The proposed architecture has a good scalability with respect to the number of processors and input bandwidth when the size of reference block and search range change.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.991-999
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• 2010

In this paper, we propose a fast motion estimation algorithm for video encoding. Conventional fast motion estimation algorithms have a serious problem of low prediction quality in some frames. However, full search based fast algorithms have low computational reduction ratio. In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution probability of motion vectors and adaptive search patterns and block matching criteria. By taking different search patterns and error criteria of block matching according to distribution probability of motion vectors, we can reduces only unnecessary computations efficiently. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2 or MPEG-4 AVC standards.

• 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.

• Journal of the Korean Society for Library and Information Science
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• v.30 no.2
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• pp.51-86
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• 1996

The primary purpose of this study is to verify the difference of behavioural characteristics between the subject specialists and professional searchers in searching full-text databases. The major findings and conclusions from this study are summarized as follows. Analyses of Search questions(the degree of understanding with search questions, the degree of difficulty in selecting terms, and the degree of expectation of search results), search processes(the number of search terms used, the number of Boolean operators and qualifiers used, the number of documents browsed and the search time(the connecting time, time to spend per one output document, time to spend per one relevant output document) and search results(the searching efficiency(the number of relevant documents, the ,recall ratio and the precision ratio), the search cost(the total search cost. the search cost per one output document and the search cost per one relevant output document) and the degree of satisfaction with search results) are significantly different between the subject specialists and professional searchers in searching full-text databases.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.33-38
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• 2020

Elasticsearch is an open source search and analytics engine that can search petabytes of data in near real time. It is designed as a distributed system horizontally scalable and highly available. It provides RESTful APIs, thereby making it programming-language agnostic. Full text search of multilingual text requires language-specific analyzers and field mappings appropriate for indexing and searching multilingual text. Additionally, a language detector can be used in conjunction with the analyzers to improve the multilingual text search. Elasticsearch provides more than 40 language analysis plugins that can process text and extract language-specific tokens and language detector plugins that can determine the language of the given text. This study investigates three different approaches to index and search Chinese, Japanese, and Korean (CJK) text (single analyzer, multi-fields, and language detector-based), and identifies the advantages of the language detector-based approach compared to the other two.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.162-165
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• 2010

In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. In the proposed algorithm, we can reduces only unnecessary computations efficiently by taking different search patterns and error criteria of block matching according to distribution probability of motion vectors. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2/4 AVC standards.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.388-396
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• 2003

In this paper, a fast motion search algorithm that performs motion search for variable blocks in integer pixel unit is proposed. The proposed method is based on the successive elimination algorithm (SEA) using sum norms to find the best estimate of motion vector and obtains the best estimate of the motion vectors of blocks, including 16${\times}$8, 8${\times}$16, and 8${\times}$8, by searching eight pixels around the best motion vector of 16${\times}$16 block obtained from all candidates. And the motion vectors of blocks, including 8${\times}$4, 4${\times}$8, and 4${\times}$4, is obtained by searching eight pixels around the best motion vector of 8${\times}$8 block. The proposed motion search is applied to the H.264 encoder that performs variable blocks motion estimation (ME). In terms of computational complexity, the proposed search algorithm for motion estimation (ME) calculates motion vectors in about 23.8 times speed compared with the spiral full search without early termination and 4.6 times speed compared with the motion estimation method using hierarchical sum of absolute difference (SAD) of 4${\times}$4 blocks, while it shows 0.1dB∼0.4dB peak signal-to-noise ratio (PSNR) drop in comparison to the spiral full search.