• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.295-301
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• 2018

Smartphone can save many data because it provide various function such as call, message, calendar, document, camera, and so on. They include a number of important things like personal information. Thus it is necessary to backup the data to deal with smartphone change and a threat like ransomware. In this paper, we analyze the backup method using PC among several backup methods and check the possibility of leakage of personal information such as contacts from backup file. It is expected to be used to check the problems of the PC backup method or to strengthen the more secure backup technology.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.117-127
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• 2005

Proportionately with a rapid development of mobile instrument technology, the number of mobile contents utilizing computing environment's graphic technology or image processing is increasing. In this paper, I designed a middleware which supports facial detection and recognition system based WIPI(Wireless Internet Platform for Interoperability), the Korean standard mobile platform. The facial recognition middleware introduced the object oriented concepts, to apply to recognition security and other contents by using mobile camera. This can reduce the development time and cost by dividing process while developing software. Therefore, it would be applied to content security or technology transfer with other company. Facial recognition middleware system is composed of face detection module and face recognition module, and proposes the application contents design method based on WIPI platform.

• Convergence Security Journal
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• v.14 no.2
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• pp.73-79
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• 2014

In the 21st century, the higher CCTV, hidden Camera, and surveillance and contra-surveillance in Cyber-space are, the higher the voices of concern about surveillance society nationally are. Nevertheless, phenomenon of panoptisme is becoming into general use. Actually, this watching system should be on the rise but this is the output playing up and advertising the positive effect of immediate convenience and offering safety that government and business made. Thus, this study wants to offer implication to warn the invasion of privacy and generalization controlled society as pointed out cause and problem of the surveillance society time according to the digital era.

• Convergence Security Journal
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• v.11 no.6
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• pp.17-23
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• 2011

In this paper, we propose mobile Augmented Reality(AR) for smart learning system which is advanced e-learning. AR is technology that seamlessly overlays computer graphics on the real world. AR has become widely available because of mobile AR. Mobile AR is possible to get information from real world anytime, anywhere. Nowadays, there are various areas using AR such as entertainment, marketing, location-based AR. One of the most promising areas is education. AR in education shows lifelike images to users for realism. It's a good way for improving concentration and attention. We utilize only a camera for image-based AR without other sensor.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.39-47
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• 2016

This study is a smart tourism research based on face recognition applied system that manages individual information of foreign tourists to smartphone. It is a way to authenticate by using face recognition, which is biometric information, as a technology applied to identification inquiry, immigration control, etc. and it is designed so that tourism companies can provide customized service to customers by applying algorism to smartphone. The smart tourism system based on face recognition is a system that prepares the reception service by sending the information to smartphone of tourist service company guide in real time after taking faces of foreign tourists who enter Korea for the first time with glasses attached to the camera. The smart tourism based on face recognition is personal information recognition technology, speech recognition technology, sensing technology, artificial intelligence personal information recognition technology, etc. Especially, artificial intelligence personal information recognition technology is a system that enables the tourism service company to implement the self-promotion function to commemorate the visit of foreign tourists and that enables tourists to participate in events and experience them directly. Since the application of smart tourism based on face recognition can utilize unique facial data and image features, it can be beneficially utilized for service companies that require accurate user authentication and service companies that prioritize security. However, in terms of sharing information by government organizations and private companies, preemptive measures such as the introduction of security systems should be taken.

• Current Optics and Photonics
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• v.1 no.2
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• pp.90-94
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• 2017

Visible light identification (VLID) is a user identification system for a door lock application using smartphone that adopts visible light communication (VLC) technology with the objective of high security, small form factor, and cost effectiveness. The user is verified by the identification application program of a smartphone via fingerprint recognition or password entry. If the authentication succeeds, the corresponding encoded visible light signals are transmitted by a light emitting diode (LED) camera flash. Then, only a small size and low cost photodiode as an outdoor interface converts the light signal to the digital data along with a comparator, and runs the authentication process, and releases the lock. VLID can utilize powerful state-of-the-art hardware and software of smartphones. Furthermore, the door lock system is allowed to be easily upgraded with advanced technologies without its modification and replacement. It can be upgraded by just update the software of smartphone application or replacing the smartphone with the latest one. Additionally, wireless connection between a smartphone and a smart home hub is established automatically via Bluetooth for updating the password and controlling the home devices. In this paper, we demonstrate a prototype VLID door lock system that is built up with LEGO blocks, a photodiode, a comparator circuit, Bluetooth module, and FPGA board.

• Convergence Security Journal
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• v.8 no.4
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• pp.161-166
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• 2008

This paper proposes a new approach to align 3D data sets by using curvatures of feature surface. We use the Gaussian curvatures and the covariance matrix which imply the physical characteristics of the model to achieve registration of unaligned 3D data sets. First, the physical characteristics of local area are obtained by the Gaussian curvature. And the camera position of 3D range finder system is calculated from by using the projection matrix between 3D data set and 2D image. Then, the physical characteristics of whole area are obtained by the covariance matrix of the model. The corresponding points can be found in the overlapping region with the cross-projection method and it concentrates by removed points of self-occlusion. By the repeatedly the process discussed above, we finally find corrected points of overlapping region and get the optimized registration result.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.989-995
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• 2015

Due to the recent increase of the importance and demand of security services, the importance of a surveillance monitor system that makes an automatic security system possible is increasing. As the market for surveillance monitor systems is growing, price competitiveness is becoming important. As a result of this trend, surveillance monitor systems based on an embedded system are widely used. In this paper, an object detection algorithm based on an embedded system for a surveillance monitor system is introduced. To apply the object detection algorithm to the embedded system, the most important issue is the efficient use of resources, such as memory and processors. Therefore, designing an appropriate algorithm considering the limit of resources is required. The proposed algorithm uses two background models; therefore, the embedded system is designed to have two independent processors. One processor checks the sub-background models for if there are any changes with high update frequency, and another processor makes the main background model, which is used for object detection. In this way, a background model will be made with images that have no objects to detect and improve the object detection performance. The object detection algorithm utilizes one-dimensional histogram distribution, which makes the detection faster. The proposed object detection algorithm works fast and accurately even in a low-priced embedded system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1141-1147
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• 2017

An unmanned aerial vehicle(UAV), commonly known as a drone, is an aircraft without a human pilot aboard, which is operated by wireless device. A drone provides the capability for the aerial search and traffic control as a police equipment. It has benefits for the missions for the aerial photography with the high resolution camera which can replace eye-dependent search processes. Moreover it has advantage of retrieving several times for the recorded videos. However, if the law enforcement agency misuse and overuse a drone for investigations and search missions without certain regulations and principles, it breaches privacy and personal information infringement. In this paper, we issue a lawful challenges on drone operations and discuss solutions to those challenges.