• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.309-314
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• 2010

In this paper, an intelligent security camera over internet is proposed. Among ISC methods, watersheds based methods produce a good performance in segmentation accuracy. But traditional watershed transform has been suffered from over-segmentation due to small local minima included in gradient image that is input to the watershed transform. And a zone face candidates of detection using skin-color model. last step, face to check at face of candidate location using SVM method. It is extract of wavelet transform coefficient to the zone face candidated. Therefore, it is likely that it is applicable to read world problem, such as object tracking, surveillance, and human computer interface application etc.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1722-1728
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• 2011

The security issue in urban transit system has been widely considered as the common matters after the fire accident at Daegu subway station. The safe urban transit system is highly demanded because of the vast number of daily passengers, and it is one of the most challenging projects. We introduced a test model for integrated security system for urban transit system and built it at a subway station to demonstrate its performance. This system consists of cameras, sensor network and central monitoring software. We described the smart camera functionality in more detail. The proposed smart camera includes the moving objects recognition module, video analytics, video encoder and server module that transmits video and audio information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.237-239
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• 2021

Failure and malfunction of the unmanned surveillance facility cost can lead to delays occurring until the person in charge arrives at the unmanned surveillance facility, and theft, damage, and information leakage damage caused by intruders. In addition, due to equipment failure and malfunction, additional costs are incurred due to constant inspection by the manager. In this paper, in order to compensate for the malfunction of unmanned facility costs, we propose a system that diagnoses the monitoring facility in real time, displays the contents of the problem, automatically restores the facility power, and informs the person in charge of the situation by text message. The proposed system is a surveillance facility consisting of main facilities such as video equipment (CCTV), sound equipment, floodlights, etc. And SMS server that can send text messages in real time. Through experiments, the effectiveness of the proposed system was verified.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.24-32
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• 2010

In this paper we proposed an object tracking system that detects the abandoned and removed objects, which is to be used in the intelligent surveillance applications. After the GMM based background subtraction and by using histogram method, the static region is identified to detect abandoned and removed objects. Since the system is implemented on DSP chip, it operates in realtime and is programmable. The input videos used in the experiment contain various indoor and outdoor scenes, and they are categorized into three different complexities; low, midium and high. By 10 times of experiment, we obtained high detection ratio at low and medium complexity sequences. On the high complexity video, successful detection ratio was relatively low because the scene contains crowdedness and repeated occlusion. In the future work, these complicated situation should be solved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.161-168
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• 2019

Recently, video equipments such as CCTV, which is spreading rapidly, is being used as a means to monitor and cope with abnormal situations in almost governments, companies, and households. However, in most cases, since recognizing the abnormal situation is carried out by the monitoring person, the immediate response is difficult and is used only for post-analysis. In this paper, we present the results of the development of video surveillance system that automatically recognizing the abnormal situations and sending such events to the smartphone immediately using the latest deep learning technology. The proposed system extracts skeletons from the human objects in real time using Openpose library and then recognizes the human behaviors automatically using deep learning technology. To this end, we reconstruct Openpose library, which developed in the Caffe framework, on Darknet framework to improve real-time processing. We also verified the performance improvement through experiments. The system to be introduced in this paper has accurate and fast behavioral recognition performance and scalability, so it is expected that it can be used for video surveillance systems for various applications.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.209-214
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• 2018

The subway, which is an urban railway, is the core of public transportation. Urban railways are always exposed to serious problems such as theft, crime and terrorism, as many passengers use them. Especially, due to the nature of urban railway environment, the scope of surveillance is widely dispersed and the range of surveillance target is rapidly increasing. Therefore, it is difficult to perform comprehensive management by passive surveillance like existing CCTV. In this paper, we propose the implementation, design method and object recognition algorithm for intelligent object recognition system in urban railway. The object recognition system that we propose is to analyze the camera images in the history and to recognize the situations where there are objects in the landing area and the waiting area that are not moving for more than a certain time. The proposed algorithm proved its effectiveness by showing detection rate of 100% for Selected area detection, 82% for detection in neglected object, and 94% for motionless object detection, compared with 84.62% object recognition rate using existing Kalman filter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.661-664
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• 2009

Recently, intelligent surveillance camera systems are needed popularly. However, current researches are focussed on improvement of a single module rather than implementation of an integrated system. In this paper, we implemented a moving wireless surveillance camera system which is composed of face detection, and using motion sensor. In our implementation, we used a camera module from SHARP, a pair of wireless video transmission module from ECOM, body of moving robot used for A4WD1 Combo kit for RC, a pair of ZigBee RF wireless transmission module from ROBOBLOCK, and a motion sensor module (AMN14111) from PANASONIC. We used OpenCV library for face dection and MFC for implement software. We identified real-time operations of face detection, PTT control, and motion sensor detecton. Thus, the implemented system will be useful for the applications of remote control, human detection, and using motion sensor.

• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1266-1275
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• 2019

With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3220-3226
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• 2011

In order to monitor internal risk factors such as fire, terror, etc. on the subway station, the surveillance systems using CCTV and various kinds of sensors have been implemented and recently, introduction of surveillance systems using an advanced IT technology, sensor network technology is tried on several areas. Since 2007, Korean government has made an effort to develop the intelligent surveillance and monitoring system, which can monitor fire, intrusion, passenger congestion, health-state of structure, etc., by using wireless sensor network technology and intelligent video analytic technique. For that purpose, this study carried out field wireless communication environment test on Chungmuro Station of Seoul Metro on the basis of ZigBee that is considered as a representative wireless sensor network before field application of the intelligent integrated surveillance system being developed, arranged and analyzed and ZigBee based wireless communication environment test results on the platform and waiting room of Chungmuro Station on this paper. Results of wireless spectrum analysis on the platform and waiting room showed that there is no radio frequency overlapped with that of ZigBee based sensor network and no frequency interference with adjacent frequencies separated 10MHz or more. As results of wireless data transmission test using ZigBee showed that data transmission is influenced by multi-path fading effect from the number and flow rate of passengers on the platform or the waiting room rather than effects from entrance and exit of the train to/from the platform, it should be considered when implementing the intelligent integrated surveillance system on the station.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.