• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.10 s.352
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• pp.60-68
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• 2006

OFDM(Orthogonal Frequency Division Multiplexing) is widely used in wideband wireless communication systems due to its excellentperformance. One of the most important operations in the OFDM receivers is preamble detection. This paper presents a differential detection method with moving average filter, which is similar to extended differential detection, and a filter determination method to achieve the best performance invarious environments. The proposed method show that the optimal filter size decreases as the delay spread increases and as the signal-to-noise ratio increases.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.43-53
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• 2012

In the this paper, a gesture-based user interface based on object detection using predefined gesture and the tracking of the detected object is proposed. For object detection, moving objects in a frame are computed by comparing multiple previous frames and predefined gesture is used to detect the target object among those moving objects. Any object with the predefined gesture can be used to control. We also propose an object tracking algorithm, namely density based meanshift algorithm, that uses color distribution of the target objects. The proposed object tracking algorithm tracks a target object crossing the background with a similar color more accurately than existing techniques. Experimental results show that the proposed object detection and tracking algorithms achieve higher detection capability with less computational complexity.

• Journal of Drive and Control
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• v.19 no.3
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• pp.23-31
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• 2022

Traffic safety issues have recently been seriously magnified, due to child deaths in apartment complexes and parking lots. Accordingly, traffic safety technologies are being developed to recognize dangerous situations on living roads and to provide warning services. In this study, a collision detection algorithm was developed to prevent collision accidents between moving objects, by using object type and location information provided from CCTV monitoring devices. To determine the exact collision between moving objects, an object movement model was developed to predict the range of movement by considering the moving characteristics of the object, and a collision detection algorithm was developed to efficiently analyze the presence and location of the collision. The developed object movement model as well as the collision detection algorithm were simulated, in a virtual space of an actual living road to verify performance and derive supplementary matters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2669-2688
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• 2016

An efficient and effective unsupervised single moving object detection framework is presented in this paper. Given the sparsely labelled trajectory points, we adopt a coarse-to-fine strategy to detect and segment the foreground from the background. The superpixel level coarse segmentation reduces the complexity of subsequent processing, and the pixel level refinement improves the segmentation accuracy. A distance measurement is devised in the coarse segmentation stage to measure the similarities between generated superpixels, which can then be used for clustering. Moreover, a Quadmap is introduced to facilitate the refinement in the fine segmentation stage. According to the experiments, our algorithm is effective and efficient, and favorable results can be achieved compared with state-of-the-art methods.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.125-131
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• 1999

In this paper, the algorithms which can track the two dimensional moving circular object using simple vision system are described. In order to track the moving object, the process of finding the object feature points - such as centroid of the object, corner points, area - is indispensable. With the assumption of two-dimensional circular moving object, the centroid of the circular object is computed from three points on the object circumference. Different kinds of algorithms for computing three edge points - simple x directional detection method, stick method. T-shape method are suggested. Through the computer simulation and experiments, three algorithms are compared from the viewpoint of detection accuracy and computational time efficiency.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.46-53
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• 2015

This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.3 no.2
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• pp.42-50
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• 2004

This paper describes a new approach to Internet host mobility. We argue that local mobility, the performance of existing mobile host protocol can be significantly improved. It proposes Fast Moving Detection schemethat based on neighbor AP channel information and moving detection table. And, it composes Local Area Clustering Path (LACP) domain that collected in AP's channel information and MN interface information. It stored the roaming table to include channel information and moving detection. Those which use the proposal scheme will need to put LACP information into the beacon or probe frame. Each AP uses scheme to inform available channel information to MN. From the simulation result, we show that the proposed scheme is advantageous over the legacy schemes in terms of theburst blocking probability and the link utilization.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.160-168
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• 2001

Change detection using difference picture has been used to detect the location of moving targets and to track them. This method needs the assumption of static camera, and the global motion compensation is required in case of a moving camera. This paper suggests a method for finding a minimum bounding rectangles(MBR) of moving targets in the image sequences using moving region detection, especially with a moving camera. If the global motion parameter is inaccurately estimated, the estimated locations of targets will be accurate either To alleviate this problem, we introduce the concept of the confidence measure and achieve more accurate estimation of global motion. Experimental results show that the proposed method successfully removes background region and extracts MBRs of the targets. Even with a moving camera, the new global motion estimation algorithm performs more precise]y and it reduces the background compensation errors of change detection.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.41-49
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• 2012

This paper proposes a detection method of wipes including horizontal wipes with linear moving borders, such as horizontal or vertical wipes, Barn Doors, and Iris Rounds with circular moving borders. The suggested method first obtains a difference image between two adjacent frames, and extracts lines and circles by applying Hough transformation to the extracted difference image. Then, we detect wipe transitions by employing an evaluation function that analyzes the number of moving trajectories of lines or circles, their moving direction and magnitude. To evaluate the performance of the suggested algorithm, experimental results show that the proposed method can effectively detect wipe transitions with linear and circular moving borders rather than some existing methods.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1128-1141
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• 2010

This paper proposes a method of moving object detection in crowded scene using clustered trajectory. Unlike previous appearance based approaches, the proposed method employes motion information only to isolate moving objects. In the proposed method, feature points are extracted from input frames first and then feature tracking is followed to create feature trajectories. Based on an assumption that feature points originated from the same objects shows similar motion as the object moves, the proposed method detects moving objects by clustering trajectories of similar motions. For this purpose an energy function based on spatial proximity, motion coherence, and temporal continuity is defined to measure the similarity between two trajectories and the clustering is achieved by minimizing the energy function in CRFs (conditional random fields). Compared to previous methods, which are unable to separate falsely merged trajectories during the clustering process, the proposed method is able to rearrange the falsely merged trajectories during iteration because the clustering is solved my energy minimization in CRFs. Experiment results with three different crowded scenes show about 94% detection rate with 7% false alarm rate.