• The Journal of Korean Institute of Information Technology
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• v.17 no.10
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• pp.101-113
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• 2019

Recently, the intelligent video surveillance technology has become able to provide various services such as predictive surveillance that have not been provided previously. Securing the security of the intelligent video surveillance is essential, and malicious manipulation of the original CCTV video data can lead to serious social problems. Therefore, in this paper, we proposed an intelligent video surveillance environment based on blockchain. The proposed scheme guarantees the integrity of the CCTV image data and protects the ROI privacy through the edge blockchain, so there is no privacy exposure of the object. In addition, it is effective because it is possible to increase the transmission efficiency and reduce storage by enabling video deduplication.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.11-20
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• 2015

In this paper, we develop an intelligent mobile surveillance system based on binary CDMA for the unmanned automatic tracking and surveillance. That is, we implement a intelligent surveillance system using the binary CDMA wireless communication technology which is applied the merit of CDMA and TDMA on it complexly. This system is able to monitor the site of the accident on network in real time and process the various situations by implementing the security surveillance system. This system pursues an object by the 360-degree using camera, expands image using a PTZ(Pan/Tilt/Zoom) camera zooming function, identifies the mobile objects image within a screen and transfers the identified image to the remote site. Finally, we show the efficiency of the implemented system through the simulation of the controlled situations, such as tracking coverage on objects, object expansion, object detection number, monitoring the remote transferred image, number of frame per second by the image output signal etc..

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.23-29
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• 2009

Blob detection is an essential ingredient process in some computer applications such as intelligent visual surveillance. However, previous blob detection algorithms are still computationally heavy so that supporting real-time multi-channel intelligent visual surveillance in a workstation or even one-channel real-time visual surveillance in a embedded system using them turns out prohibitively difficult. In this paper, we propose a fast and precise blob detection algorithm for visual surveillance. Blob detection in visual surveillance goes through several processing steps: foreground mask extraction, foreground mask correction, and connected component labeling. Foreground mask correction necessary for a precise detection is usually accomplished using morphological operations like opening and closing. Morphological operations are computationally expensive and moreover, they are difficult to run in parallel with connected component labeling routine since they need much different processing from what connected component labeling does. In this paper, we first develop a fast and precise foreground mask correction method utilizing on neighbor pixel checking which is also employed in connected component labeling so that the developed foreground mask correction method can be incorporated into connected component labeling routine. Through experiments, it is verified that our proposed blob detection algorithm based on the foreground mask correction method developed in this paper shows better processing speed and more precise blob detection.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.111-114
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• 2008

보안이 중요시 되는 공간에서 지능형 감시 시스템의 필요성이 점차 중요시 되고 있다. 본 논문에서는 embedded Linux 기반의 Mobile Robot에 Network Camera를 탑재 하여 침입자를 추적할 수 있는 시스템 구현에 목적을 두고 있다. Network Camera부터 Wireless Lan을 이용하여 서버로 영상을 전송하고, 서버에서 블록매칭 알고리즘을 이용하여 침입자의 이동경로를 파악하며 침입자에 대한 방향 정보를 전송하여 침입자를 추적한다. 로봇이 침입자를 추적함에 따라 침입자의 유효 영상을 얻는다. 본 논문에 의해서 구현된 시스템은 다른 감시 시스템과 연동하여 지능형 감시 시스템으로서 신뢰성을 더할 수 있다.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.209-217
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• 2012

In the present, Wireless Sensor Network(WSN) has been used for the purpose of the military operation with surveillance systems and for collecting useful information from the natural environment. Basically, low-power, easy deployment and low cost are the most important factors to be deployed for WSNs. Lots of researches have been studied to meet those requirements, especially on the node capacity and battery lifetime improvements. Recently, the study of wireless mesh networks applied into the surveillance systems has been proceeded as a solution of easy deployment. In this paper, we proposed large-scale intelligent multi-layer surveillance systems based on QoS assuring Wireless Mesh Networks and implemented them in the real testbed environment. The proposed system explains functions and operations for each subsystem as well as S/W and H/W architectures. Experimental results are shown for the implemented subsystems and the performance is satisfactory for the surveillance system. We can identify the possibility of the implemented multi-layer surveillance system to be used in practice.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.35-41
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• 2015

When a video surveillance system tracks a specific object, it is very important to get quickly the information of the object through fast image processing. Usually one camera surveillance system for tracking the object made results in various problems such like occlusion, image noise during the tracking process. It makes difficulties on image based moving object tracking. Therefore, to overcome the difficulties the multi video surveillance system which installed several camera within interested area and looking the same object from multi angles of view could be considered as a solution. If multi cameras are used for tracking object, it is capable of making a decision having high accuracy in more wide space. This paper proposes a method of recognizing and tracking a specific object like a car using the homography in which multi cameras are installed at the crossroad.

• 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.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.115-122
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• 2019

CCTV(Closed-Circuit Television) is increasingly exposed to CCTV per person as the number of installations increases every year for accident prevention and facility safety. The intelligent video surveillance system technology is attracting attention to the privacy protection of exposed subjects. The intelligent video surveillance system performs a process for the privacy protection so as to perform the action type of the subject and the judgment of the situation in the simple identification of the photographed image data, or to prevent the information, from which the information of the photographed subject is exposed. The proposed technique is applied to the video surveillance system and converts the original image information taken from the video surveillance system into similar image information so that the original image information is not leaked to the outside. In this paper, we propose an image conversion mechanism that inserts a virtual face image that approximates a preset similarity.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.866-871
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• 2009

In this paper, we introduced design of intelligent surveillance camera system and typical event processing scenario for urban transit. To analyze video, we studied events that frequently occur in surveillance camera system. Scenario is designed for estimation in the case of seven representative situations(designated area invasion, an object left alone, removed object in designated area, object tracking, loitering and congestion measurement) in urban transit. Our system is optimized for low hardware complexity, real time processing and scenario dependent solution.

• ETRI Journal
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• v.37 no.3
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• pp.551-561
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• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.