• 인지과학
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• 제14권3호
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• pp.1-11
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• 2003

정지/운동하는 배경자극들 속에서 정지/운동하는 표적을 탐지하는 데 있어서 표적 유형과 망막 이심율의 효과를 알아보기 위해서 두 가지 실험을 수행하였다. 두 실험 모두 시각탐색과제를 사용하였다. 망막 이심율은 1.6$^{\circ}$ 단위로 커지는 5개의 동심원으로 구분하였으며, 표적은 배경자극과 방위차원에서 차이나는 방위 표적과 세부특정에서 차이나는 세부특정 표적이었다. 실험 l에서는 표적과 배경자극이 모두 정지되어있는 상황에서의 탐색을 다루었다. 그 결과 표적 유형과 망막 이심율 사이에 상호작용이 있었다. 정지상황에서 방위 표적은 망막 이심율의 영향을 별로 받지 않는 반면에, 세부특정 표적은 망막 이율이 증가함에 따라서 탐지시간이 일관성 있게 증가하였다. 표적과 배경자극이 모두 운동하는 상황인 실험 2 에서도 둘 사이의 상호작용이 나타냈으나, 그 이유는 실험 1과 극적인 대조를 이루었다. 즉, 운 동 상황에서 방위 표적은 망막 이심율이 증가함에 따라서 탐지시간이 일관성 있게 감소하는 반면, 세부 특징 표적은 망막 이심율의 영향을 거의 받지 않았다. 두 실험의 결과를 항공기나 자동차의 운동과 같은 현실상황과 관련된 합의와 문제점 그리고 향후 연구방향을 논의하였다.

• 한국멀티미디어학회논문지
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• 제22권10호
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• pp.1178-1186
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• 2019

In recent years, interest in drones has grown, and many countries are developing them into a strategic industry of the future. Drones are not only used in industries such as logistics and agriculture but also in various public sectors such as life rescue, disaster investigation, traffic control, and firefighting. One of the most important tasks of a drone is to accurately identify targets in these applications. Target recognition may vary depending on the search environment of the drone. Therefore, this study tests and analyzes the drone's target recognition performance according to changes in the search environment such as the search altitude and the search angle. In addition, we propose a new algorithm that improves upon the disadvantages of the Haar cascade method, which is the existing algorithm that recognizes the target by analyzing a captured image.

• 한국경영과학회지
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• 제19권1호
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• pp.201-206
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• 1994

The linear search problem is concerned with finding a hiden target on the real line R. The position of the target governed by some probability distribution. It is desired to find the target in the least expected search time. This problem has been formulated as an optimization problem by a number of authors without making use of Markov Decision Process (MDP) theory. It is the aim of the paper to give a (MDP) formulation to the search problem which we feel is both natural and easy to follow.

• 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.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.639-647
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• 2020

In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Journal of Information Technology Applications and Management
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• 제10권2호
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• pp.33-41
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• 2003

It is not easy to find desired information in the world wide web. In this research, we introduce a notion of concept network that is useful in finding information if it is used in search engines that are specialized in domains such as medicine, law or engineering. The concept network that we propose is a network in which nodes represent significant concepts in the domain, and links represent relationships between the concepts. We may use the concept network constructor as a preprocessor to speci-alized search engines. When user enters a target word to find information, our system generates and displays a concept network in which nodes are con-cepts that are closely related with the target word. By reviewing the network, user may confirm that the target word is properly selected for his intention, otherwise he may replace the target word with better ones discovered in the network. In this research, we propose a detailed method to construct concept net-work, implemented a prototypical system that constructs concept networks, and illustrate its usefulness by demonstrating a practical case.

• 대한안전경영과학회지
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• 제15권4호
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• pp.289-294
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• 2013

Due to sudden transition to intellectual society corresponding with fast technology progress, companies and nations need to focus on development and guarantee of intellectual property. The possession of intellectual property has been the important factor of competition power. In this paper we developed the efficient patent search process with big data analysis tool R. This patent search process consists of 5 steps. We result that at first this process obtain the core patent search key words and search the target patents through search formula using the combination of above patent search key words.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.677-680
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• 2003

Perceptual landmarks are an effective solution for a mobile robot realizing steady and reliable long distance navigation. But the prerequisite is those landmarks must be detected and recognized robustly at a higher speed under various lighting conditions. This made image processing more complicated so that its speed and reliability can not be both satisfied at the same time. Color based target detection technique can separate target color regions from non-target color regions in an image with a faster speed, and better results were obtained only under good lighting conditions. Moreover, in the case that there are other things with a target color, we have to consider other target features to tell apart the target from them. Such thing always happens when we detect a target with its single character. On the other hand, we can generally search for only one target for each time so that we can not make use of landmarks efficiently, especially when we want to make more landmarks work together. In this paper, by making use of the moment invariants of each landmark, we can not only search specified target from separated color region but also find multi-target at the same time if necessary. This made the finite landmarks carry on more functions. Because moment invariants were easily used with some low level image processing techniques, such as color based target detection and gradient runs based target detection etc, and moment invariants are more reliable features of each target, the ratio of target detection were improved. Some necessary experiments were carried on to verify its robustness and efficiency of this method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.311-312
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• 2007

This dissertation proposes a global search and a local search method to track the object in real-time. The global search recognizes a target object among the candidate objects through the entire image search, and the local search recognizes and track only the target object through the block search. This dissertation uses the object color and feature information to achieve fast object recognition. Finally we conducted an experiment for the object tracking system based on a pan/tilt structure.