• Journal of Digital Convergence
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• v.13 no.9
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• pp.183-189
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• 2015

In this paper, we propose an object tracking method using the color information of the image in surveillance network. This method perform a object detection using of adaptive color model. Object contour detection plays an important role in application such as object recognition. Experimental results demonstrate successful object detection over a wide range of object's variation in color and scale. In applications to detect an object in real time, when transmitting a large amount of image data it is possible to find the mode of a color distribution. The specific color of an object is modified at dynamically changing color in image. So, this algorithm detects the tracking area information of object within relevant tracking area and only tracking the movement of that object.Through experiments, we show that proposed method is more robust than other methods under certain ideal situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3159-3176
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• 2014

This work presents an analysis of the buffer features of an access router, especially the size, the impact on delay and the packet loss rate. In particular, we study how these features can affect the Quality of Service (QoS) of multimedia applications when generating traffic bursts in local networks. First, we show how in a typical SME (Small and Medium Enterprise) network in which several multimedia flows (VoIP, videoconferencing and video surveillance) share access, the upgrade of the bandwidth of the internal network may cause the appearance of a significant amount of packet loss caused by buffer overflow. Secondly, the study shows that the bursty nature of the traffic in some applications traffic (video surveillance) may impair their QoS and that of other services (VoIP and videoconferencing), especially when a certain number of bursts overlap. Various tests have been developed with the aim of characterizing the problems that may appear when network capacity is increased in these scenarios. In some cases, especially when applications generating bursty traffic are present, increasing the network speed may lead to a deterioration in the quality. It has been found that the cause of this quality degradation is buffer overflow, which depends on the bandwidth relationship between the access and the internal networks. Besides, it has been necessary to describe the packet loss distribution by means of a histogram since, although most of the communications present good QoS results, a few of them have worse outcomes. Finally, in order to complete the study we present the MOS results for VoIP calculated from the delay and packet loss rate.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.626-633
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• 2009

Lawful interception (LI) involves legally accessing private communication such as telephone calls or email messages. Numerous countries have been drafting and enacting laws concerning the LI procedures. With the proliferation of portable Internet services such as the IEEE 802.16e wireless mobile networks, surveillance over illegal users is an emerging technical issue in LI. The evermigrating users and their changing IP's make it harder to provide support for seamless LI procedures on 802.16e networks. Few studies, however, on seamless LI support have been conducted on the 802.16e mobile networks environments. Proposed in this paper are a seamless LI architecture and algorithms for the 802.16e networks. The simulation results demonstrate that the proposed architecture improves recall rates in intercepting mobile user, when compared to the existing LI architectures.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.83-90
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• 2012

In this paper, an intelligent visual surveillance system based on a NIOS II embedded platform is implemented. By this time, embedded based visual surveillance systems were restricted for a special purpose because of high dependence upon hardware. In order to improve the restriction, we implement a flexible embedded platform, which is available for various purpose of applications. For high speed processing of software based programming, we improved performance of the system which is integrated the SOPC type of NIOS II embedded processor and image processing algorithms by using software programming and C2H(The Altera NIOS II C-To-Hardware(C2H) Acceleration Compiler) compiler in the core of the hardware platform. Then, we constructed a server system which globally manage some devices by the NIOS II embedded processor platform, and included the control function on networks to increase efficiency for user. We tested and evaluated our system at the designated region for visual surveillance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1453-1458
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• 2009

Sensor network for the human approach in a difficult area and a wide range of surveillance and the boundaries for the purpose and mission is the utilization significantly. In this paper we searched important nodes from the surveillance reconnaissance sensor network based on the virtual data. we generated data within the sensor's measurement range in the data transmitted from sensor nodes, and used PCA(Principle Component Analysis) for searching key node. If the important sensor node searched, and we can have easy management and establishing security measures when security problems is happened about nodes. This is for the sensor network in terms of effectiveness and cost-effectively and is directly connected with life span.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1091-1092
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• 2007

Wireless sensor networks (WSN) can be used in military surveillance, in which highly confidential data needs to be transmitted. In effect, security becomes a very important aspect in such networks. We present an efficient key management scheme for WSN. Our scheme is an improvement over SHELL [1] and mostly relies on communication within a cluster of nodes.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.45-54
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• 2018

This paper presents a vision-based fall detection system to automatically monitor and detect people's fall accidents, particularly those of elderly people or patients. For video analysis, the system should be able to extract both spatial and temporal features so that the model captures appearance and motion information simultaneously. Our approach is based on 3-dimensional convolutional neural networks, which can learn spatiotemporal features. In addition, we adopts a thermal camera in order to handle several issues regarding usability, day and night surveillance and privacy concerns. We design a pan-tilt camera with two actuators to extend the range of view. Performance is evaluated on our thermal dataset: TCL Fall Detection Dataset. The proposed model achieves 90.2% average clip accuracy which is better than other approaches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.896-898
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• 2012

Recently, many countries are making efforts for the development of ocean resources because the necessity and importance of the ocean resources are increased. Underwater sensor networks have emerged as a very powerful technique for many applications, including monitoring, measurement, surveillance and control and envisioned to enable applications for oceanographic data collection, ocean sampling, environmental and pollution monitoring, offshore exploration, disaster prevention, tsunami and seaquake warning, assisted navigation, distributed tactical surveillance, and mine reconnaissance. The idea of applying sensor networks into underwater environments (i.e., forming underwater sensor networks) has received increasing interests in monitoring aquatic environments for scientific, environmental, commercial, safety, and military reasons. The data obtained by observing around the environment are wireless-transmitted by a radio set with various waves. According to the technical development of the medium set, some parameters restricted in observing the ocean have been gradually developed with the solution of power, distance, and corrosion and watertight by the seawater. The actual matters such as variety of required data, real-time observation, and data transmission, however, have not enough been improved just as various telecommunication systems on the land. In this paper, a wireless management system will be studied through a setup of wireless network available at fishery around the coast, real-time environmental observation with RF sensor, and data collection by a sensing device at the coastal areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.597-611
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• 2009

With the advent of ubiquitous computing society, many advanced technologies have enabled wireless sensor networks which consist of small sensor nodes. However, the sensor nodes have limited computing resources such as small size memory, low battery life, short transmission range, and low computational capabilities. Thus, decreasing energy consumption is one of the most significant issues in wireless sensor networks. In addition, numerous applications for wireless sensor networks are recently spreading to various fields (health-care, surveillance, location tracking, unmanned monitoring, nuclear reactor control, crop harvesting control, u-city, building automation etc.). For many of them, supporting security functionalities is an indispensable feature. Especially in case wireless sensor networks should provide a sufficient variety of security functions, sensor nodes are required to have more powerful performance and more energy demanding features. In other words, simultaneously providing security features and saving energy faces a trade-off problem. This paper presents a novel energy-efficient security architecture in an IEEE 802.15.4-based wireless sensor network called the Hybrid Adaptive Security (HAS) framework in order to resolve the trade off issue between security and energy. Moreover, we present a performance analysis based on the experimental results and a real implementation model in order to verify the proposed approach.