• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.9-12
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• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.7-10
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• 2000

Fast block motion estimation technique is proposed to reduce the computational complexity in video coding. In the conventional methods the size of search region is fixed. For small motion regions like background the small size of sea of search region is enough to find a block motion. But for active motion regions the large size of search region is preferred to figure out the accurate motion vector. Therefore, it is reasonable that a block motion is estimated in the variable search region (both the size and the position of it). That is to say, the search region varies according to the predicted motion characteristics of a block. The block motion in video frames has temporal continuity and then the search region of a current block is predicted using the block motion of previous blocks. The computational complexity of the proposed technique is significantly reduced with a good picture quality compared to the conventional methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.843-846
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• 2000

An optical flow-based motion estimation algorithm is proposed for video coding. The algorithm uses block-matching motion estimation with an adaptive search region. The search region is computed from motion fields that are estimated based on the optical flow. The algorithm is based on the fact that true block-motion vectors have similar characteristics to optical flow vectors. Thereafter, the search region is computed using these optical flow vectors that include spatial relationships. In conventional block matching, the search region is fixed. In contrast, in the new method, the appropriate size and location of the search region are both decided by the proposed algorithm. The results obtained using test images show that the proposed algorithm can produce a significant improvement compared with previous block-matching algorithms.

• Journal of applied mathematics & informatics
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• 제27권1_2호
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• pp.233-243
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• 2009

This paper concerns an algorithm that combines line search and trust region step for nonlinear optimization problems. Unlike traditional trust region methods, we incorporate the Armijo line search technique into trust region method to solve the subproblem. In addition, the subproblem is solved accurately, but instead solved by inaccurate method. If a trial step is not accepted, our algorithm performs the Armijo line search from the failed point to find a suitable steplength. At each iteration, the subproblem is solved only one time. In contrast to interior methods, the optimal solution is derived by iterating from outside of the feasible region. In numerical experiment, we apply the algorithm to nonlinear portfolio optimization problems, primary numerical results are presented.

• Journal of applied mathematics & informatics
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• 제14권1_2호
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• pp.123-136
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• 2004

In this paper, a combining trust region and line search algorithm for equality constrained optimization is proposed. At each iteration, we only need to solve the trust region subproblem once, when the trust region trial step can not be accepted, we switch to line search to obtain the next iteration. Hence, the difficulty of repeated solving trust region subproblem in an iterate is avoided. In order to allow the direction of negative curvature, we add second correction step in trust region step and employ nonmonotone technique in line search. The global convergence and local superlinearly rate are established under certain assumptions. Some numerical examples are given to illustrate the efficiency of the proposed algorithm.

• 전자공학회논문지B
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• 제31B권8호
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• pp.129-136
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• 1994

In this paper an adaptive moving method of the search region tracking the motion is proposed. The search region in BMA is determined by the capability of hardware implementation and the degree of motion. But once determined nothing can be changed during coding procedure. In this paper we predict the level of motion of the current block using motion vectors of previous frames without overhead information and change the location of the search region according to the level of the motion predicted. In short the proposed method can be archieved the dsirable effect such that the size of search region gets large when the motion is large. Results of experiments show that prediction efficiency has been improved by using adaptive moving method resulting in reduced prediction error in the blocks with large motion.

• 전기학회논문지
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• 제58권5호
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• 한국통신학회논문지
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• 제25권1B호
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• pp.167-174
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• 2000

간단하고 점진적인 움직임 추정 알고리듬인 3단계 탐색 방법은 저비트율 영상 압축분야에서 널리 이용되어 왔다. 본 논문에서는 탐색 영역 내에서의 움직임 특성을 이용한 새로운 고속 블록 움직임 추정 알고리듬을 제안한다. 대부분의 움직임 벡터 영역의 중심 부분에 존재하며, 따라서 본 논문에서는 중심 부분의 움직임을 3단계 탐색 방법보다 훨씬 세밀하게 추정한다. 또한 각 단계에서 가능한 모든 움직임 방향을 고려하면서 이전 단계내의 탐색영역과 중첩되지 않는 국부 영역에 대해서만 움직임 추정을 행한다. 따라서 제안한 방법은 기존의 방법과 비교하여 보다 우수한 움직임 추정을 얻을 수 있으며, 계산 시간을 줄일 수 있다

• 한국정보통신학회논문지
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• 제12권7호
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• pp.1187-1192
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• 2008

본 논문은 적응적 탐색 영역과 새로운 3단계 탐색을 이용하는 고속 움직임 추정을 제안한다. 제안한 방법은 이웃 블록의 모션벡터로부터 현재 블록의 움직임를 예측하고, 예측된 움직임 정보를 이용하여 탐색 영역을 적응적으로 설정함으로써 움직임 보상 영상의 화질이 $0.43dB{\sim}2.19dB$ 향상되었다. 또한 새로운 3단계 탐색 패턴을 적용하여 블록 당 계산량을 기존의 방법에 비해 $1.3%{\sim}1.9%$ 감소시킴으로써 고속 움직임 추정이 가능함을 알 수 있었다.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권11호
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• pp.532-540
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• 2001

In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.