• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.271-274
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• 2003

This paper presents a robust error concealment method for burst-packet-loss networks. The proposed error concealment algorithm can reduce the computational complexities of the existing error concealment methods. Moreover, experimental results show that the proposed method produces the better video quality than the conventional boundary matching algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.91-98
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• 2005

In this paper, we propose a temporal error concealment method based on the edge adaptive masking. In the method, four regions around the corrupted block - top, bottom, left, and right - are defined and the edge features of the regions are extracted by applying an edge operator for each direction. The size of a mask for the boundary matching is determined by the edge information, which can be considered as a criterion to measure the activity of the boundary region. In other words, it is determined such that the size of the mask is proportional to the amount of edge-component extracted from each region in order to yield the higher reliability on boundary matching. This process is equivalent to applying weights depending on the edge features, which leads the improved motion vector. In experiments, it is verified that the proposed method outperforms the conventional methods in terms of image quality, and then its merits and demerits are discussed.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1067-1087
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• 2018

In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top area automatically due to outliers and large holes of point cloud. Thus, we propose a technique to extract building boundary semi-automatically from the DSM created from stereo images. The technique consists of watershed segmentation for using user input as markers and recursive MBR algorithm. Since the proposed method only inputs simple marker information that represents building areas within the DSM, it can create building boundary efficiently by minimizing user input.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.71-75
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• 2009

In this paper, we present a real-time method to detect moving objects in a rotating and zooming camera. It is useful for camera surveillance of fixed but rotating camera, camera on moving car, and so on. We first compensate the global motion, and then exploit the displaced frame difference (DFD) to find the block-wise boundary. For robust detection, we propose a kind of image to combine the detections from consecutive frames. We use the block-wise detection to achieve the real-time speed, except the pixel-wise DFD. In addition, a fast block-matching algorithm is proposed to obtain local motions and then global affine motion. In the experimental results, we demonstrate that our proposed algorithm can handle the real-time detection of common object, small object, multiple objects, the objects in low-contrast environment, and the object in zooming camera.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.13 no.1
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• pp.48-53
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• 2017

We diagnosed the defect using the data obtained from the nuclear power plant simulator. In this paper, we diagnosed faults in the nuclear power plant system for discovery instead of the traditional single-component or device unit. We created the six fault scenarios and used a fault simulator to obtain the fault data. It was extracted pattern from acquired failure data. Neural network model was trained and simple pattern matching algorithm was applied. We presented a simulation result and confirmed that the applied algorithm works correctly.

• Smart Media Journal
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• v.6 no.2
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• pp.9-14
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• 2017

A packet loss in wireless environments causes a severe degradation of video quality in video communications. In this paper, a novel video error concealment algorithm is presented by combining boundary errors and a block reliability measure. The block reliability measure decides the reliability of a block by checking residual errors of a block. In the proposed approach, a motion vector of a missing unreliable block in an inter coded frame is obtained initially based on the motion vector of the same block in the reference frame. Furthermore, if the block in the reference frame is unreliable according to the reliability measure, a new motion vector is decided based on block boundary errors around the initial motion vector. According to our simulations, the proposed approach shows promising results for error concealment in error-prone wireless environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1384-1392
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• 1999

A high compression rate is required to transmit video sequences over low bit rate networks such as low bit rate communication channels. When highly compressed videos are transmitted over mobile channels of high error rate, bitstreams corrupted by channel errors are not only difficult to be decoded, but also have fatal effects on the other parts of the bitstreams. In this Paper, we propose an error concealment algorithm for recovering the blocks which can not be decoded due to damaged bitstreams. The proposed error concealment algorithm recovers the damaged blocks using the information of adjacent blocks which are correctly decoded. In the proposed algorithm, the motion vector of the damaged block is estimated using the overlapped block motion compensation(OBMC) and block boundary matching(BBM) techniques. Experiment results show that the proposed algorithm exhibits better performance in PSNR than existing error concealment methods.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.134-142
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• 2019

As the 4th industry has been widely distributed, there is a need for a process of real-time image recognition in various fields such as identification of company employees, security maintenance, and development of military weapons. Therefore, in this paper, we will propose an algorithm that effectively recognizes a test object by comparing it with the DB model. The proposed object recognition system first expresses the outline of the test object as a set of vertices with the distances of predefined length or more. Then, the degree of matching of the structures of the two objects is calculated by examining the distances to the outline of the DB model from the vertices constituting the test object. Because the proposed recognition algorithm uses the outline of the object, the recognition process is easy to understand, simple to implement, and a satisfactory recognition result is obtained.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.136-150
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• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.407-416
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• 2006

It is difficult for the movement detection of an object through a camera to detect exact movement because of unnecessary noises and changes of the light. It can be recognized as a background, when there is no movement after the inflow of an object. Therefore, It is necessary to fast search algorithm for tracking and extract of object that is realtime image. In this thesis, we evaluate the difference of the input vision based on initial image and replace some pixels in process of time. When there is a big difference between background image and input image, we decide it is the point of the time of the object input and then extract boundary point of it. The extracted boundary point detects precise movement of the object by creating minimum block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the performance test.