• Journal of information and communication convergence engineering
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• 제9권3호
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• pp.319-324
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• 2011

In computing the optical flow. Horn and Schunck's method which is a representative algorithm is based on differentiation. But it is difficult to estimate the velocity for a large displacement by this algorithm. To cope with this problem multigrid method has been proposed. In this paper, we have proposed a scaled multigrid algorithm which the initial flow for a level is calculated by the summation of the optimally scaled flow and error flow. The optimally scaled flow is the scaled expanded flow of the previous level, which can generate an estimated second image having the least RMS error with respect to the original second image, and the error flow is the flow between the estimated second image (generated by the optimally scaled flow) and the original second image. The flow for this level is then estimated using the original first and second images and the initial flow for that level. From among the various coarsest starting levels of the multigrid algorithm, we select the one that finally gives the best estimated flow. Better results were achieved using our proposed method compared with Horn and Schunck's method and a conventional multigrid algorithm.

• Journal of the Optical Society of Korea
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• 제20권6호
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• pp.745-751
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• 2016

A detection algorithm, based on the combined local-global (CLG) optical-flow model and Gaussian pyramid for a moving target appearing against a dynamic background, can compensate for the inadaptability of the classic Horn-Schunck algorithm to illumination changes and reduce the number of needed calculations. Incorporating the hypothesis of gradient conservation into the traditional CLG optical-flow model and combining structure and texture decomposition enable this algorithm to minimize the impact of illumination changes on optical-flow estimates. Further, calculating optical-flow with the Gaussian pyramid by layers and computing optical-flow at other points using an optical-flow iterative with higher gray-level points together reduce the number of calculations required to improve detection efficiency. Finally, this proposed method achieves the detection of a moving target against a dynamic background, according to the background motion vector determined by the displacement and magnitude of the optical-flow. Simulation results indicate that this algorithm, in comparison to the traditional Horn-Schunck optical-flow algorithm, accurately detects a moving target undergoing illumination changes against a dynamic background and simultaneously demonstrates a significant reduction in the number of computations needed to improve detection efficiency.

• 전자공학회논문지B
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• 제28B권11호
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• pp.913-924
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• 1991

In this paper, we propose a motion estimation algorithm using hierarchical structure. The algorithm uses the image pyramids from the repetitive application of Gaussian filtering and decimation, and performs an inter-level displacement propagation in its motion estimation process. The motion estimation algorithm based on the hierarchical structure is shown to be very effective since this scheme utilizes the local imformation as well as the global imformation. The experimental results on the various data imdicate that compared to the Horn and Schunck's method, the proposed algorithm yields an accurate motion estimation with a fast convergence behaviour.

• 한국멀티미디어학회논문지
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• 제3권4호
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• pp.380-388
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• 2000

변위량을 계산하여 영상 쌍의 대응점을 추출하는 방법중에서 대표적인 Hom & Schunck 수법이 있고, 이는 미분법을 기초하기 때문에 변위가 큰 변위량 추정을 위하여는 적당치 않다. 본 논문에서는 이러한 종래의 수법으로는 계측이 곤란하였던 이동량이 큰 변위의 변위량을 추정할 수 있는 직교 함수 전개법을 제안한다. 종래의 Horn & Schunck 수법에 의한 변위량은 국소적처리를 출발점으로 하는bottom-up수법으로 구하였으나, 직교 함수 전개법에서는 이와는 반대로 영상 전체의 움직임을 직교함수의 저차 모드부터 순차 전개하는 top-down수법을 이용한다. 직교 함수 전개법을 이용하여 변위량을 구하는 방법은 명도의 적분치 불변의 구속 조건에 관한 도함수를 이용하는 투영법에 의한 반복 계산으로 얻어진다. 마지막으로 구하여진 변위량과 제1원영상으로부터 제2의 영상을 합성하고, 합성된 영상과 제2의 원영상과 NRMS오차와 상관값을 비교하여 그 유효성을 보인다.

• 한국정보통신학회논문지
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• 제11권7호
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• pp.1341-1347
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• 2007

기존의 광류 (Optical flow)는 국소적 처리를 시작점으로 하는 bottom-up수법에 의해서 구하였다. 이에 반해, 본 논문은 영상유체보존식과 함수 전개법에 의해 영상 전체의 움직임을 차수가 낮은 모드로 부터 순차적으로 전개하는 bottom-down수법을 새로운 수법으로 제안한다. 의료 영상에 있어서 명도는 움직임이 있어도 불변으로 유지하려는 경우가 많다. 그러나 이 같은 영상계열에서의 움직임은 좌표 변환에 의해서 대응된다. 본 수법의 경우 광류는 선형모멘트방정식의 함수에 관한 도함수를 이용하는 투영법에 의해서 반복계산으로 구하여 진다. 본 논문에서는 심장의 영상계열을 이용하여 기존의 Horn and Schunck기법, Standard multigrid기법과 본 수법의 알고리즘을 비교 평가하여 유효성을 나타낸다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1341-1344
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• 2015

In this paper, the designed fish robot is researched and developed for aquarium underwater robot. This paper is a study on how the outside technology merely to find the location of fish robots without specific sensor or internal devices. This model is designed to detect the position of the Robotic Fish in the Mat lab and Simulink. This intends to recognize the shape of the tank via a video device such as a camera or camcorder using an image processing technique to identify the location of the robotic fishes. Here, we are applied the two methods, one is Hom - Schunk Method and second one is newly proposed method that is the comparing image data algorithm. The Horn - Schunck Method is used to obtain the velocity for each pixel in the image and the comparing image data algorithm is proposed to obtain the position with comparing two video frames and assumes a constant velocity in each video frame.