• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.983-990
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• 2022

In this paper, we implemented a hierarchical encryption system using two-step phase-shifting digital holography(PSDH) technology based on XOR and scramble operations. The proposed encryption system is a system that authenticates access through the issuance of an encryption key for access to individual laboratories, department offices, and universities. In the encryption process, we proposed a double encryption method using XOR and scramble operation with digital technology and two-step phase-shifting digital holography with optical technology. In the two-step PSDH process, an new method of determining the reference wave intensity without measuring it by using random common object image gererated from digital encryption process was also proposed. In the decryption process, the process is performed in the reverse order of encryption process. And only when the various key information used in the encryption process is correct, the encrypted information can be decrypted, so that the user can access the desired place. That is, there is a feature that can hierarchically control the space that can be accessed according to the type of key issued in the proposed encryption system. Through the computer simulation, the feasibility of the proposed hierarchical encryption system was confirmed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.685-691
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• 1993

This paper introduces a PC-based image data processing unit that is composed of preprocessor board and main processor board; The preprocessor contains Inmos A110 processor and efficient H/W architecture for fast mask/logic operations at the speed of video signal rate. It is controlled by the main processor which communicates with the host PC. The main processor board contains TI TMS320C31 digital signal processor, and can access the frame memory of the processor for extra S/W tasks. We test 3*3, 5*5 masks and logic operations on 386/486/DSP and compare the result with that of the proposed unit. The result shows ours are extremely faster than conventional CPU based approach, that is, over several hundred times faster than even DSP.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.199-204
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• 2008

Visual surveillance is an active topic recently in Computer Vision. Event detection and recognition is one important and useful application of visual surveillance system. In this paper, we propose a new method to recognize the entering and exiting events based on the human's movement feature and the door's state. Without sensors, the proposed approach is based on novel and simple vision method as a combination of edge detection, motion history image and geometrical characteristic of the human shape. The proposed method includes several applications such as access control in visual surveillance and computer vision fields.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.107-129
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• 1996

Recently, surveillance system designed to collect various trsffic information are becoming new areas of development . Among these, the image detector is a ayatem which can measure the travel time and speed in realtime and this is emerging as the most effcient tool to be available in future related areas. But in measuring wide-area information in realtime, the image detector are yet full of problem in its accuracy. The aim of this ahesis is to develop an algorithms which can collect wide-area information such as travel time and travel speed in urban networks and freeways in realtime. The information on wide-area such as travel time and travel speed is important in accomplishing strategic function in traffic control. The algorithm developed from this study is based on the image tracking model which tracks a moving vehicle form image datas collected continuously, and is constructed to perform realtime measurement. To evaluate the performance of the developed algorithms, 600 ind vidual vehicles in total were used as data for the study, and this evaluation was carried out with the differenciation of day and night condition at the access roads in front of AJou University, In the statistical analysis results, the error rate was recorded as 5.69% and it has proved to be applicable on the field in both day and noght conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1152-1157
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• 2021

This paper proposes a face recognition method for access control of apartment building. Different from most existing face recognition methods, the proposed one does not require any manual process for face enrollment. When a person is exiting through the main entrance door, his/her face data (i.e., face image and face feature) are automatically extracted from the captured video and registered in the database. When the person needs to enter the building again, the face data are extracted and the corresponding face feature is compared with the face features registered in the database. If a matching person exists, the entrance door opens and his/her access is allowed. The face data of the matching person are immediately deleted and the database has the latest face data of outgoing person. Thus, a higher recognition accuracy could be expected. To verify the feasibility of the proposed method, Python based face recognition has been implemented and the cloud service provided by a web portal.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.159-166
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• 2010

From public insecurity, access of wealth, alteration of population structure, and changes of security recognition, physical security has been continuously developed and changed. In these days, typical systems for physical security are unmanned security system using telephone network and security equipment, image recognition system using DVR and camera, and access control system by finger print recognition and RFID cards. However, physical security system is broadening its domain towards ICT based convergence with networked camera, biometrics, individual authentication, and LBS services. This paper proposes main technical trends and various security convergences for future physical security services by classifying the security categories into 3 parts; Individual security for personal protection, IT Convergence for large buildings, and Homeland Security for omni-directional security.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.396-402
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• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1417-1426
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• 2007

As one of schemes to protect multimedia content. it is the selective encryption scheme to encrypt partially multimedia content. Compared AES(advanced encryption standard) of traditional encryption, the selective encryption scheme provides low security but is applicable to applications of multimedia content not to require high secrecy. In this paper, we improve the image scrambling scheme proposed by Van De Ville which scrambles an image without bandwidth expansion using DPSS(discrete prolate spheroidal sequence) to make it more secure based on Shujun's research which verifies the secrecy of Van De Ville's scheme. The proposed method utilizes an orthonormalized random matrix instead of Hadamard matrix for secret matrix and to add it for providing high secrecy against statistical attack or known-plaintext attack using some statistical property or estimate of secret matrix from a scrambled image. The experimental results show that the proposed method is more secure than the existing scheme. In addition, we show that the proposed method can be applied to access control or copy control of watermarking application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.355-366
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• 2022

This paper proposes a microcode-based neural network accelerator controller for artificial intelligence accelerators that can be reconstructed using a programmable architecture and provide the advantages of low-power and ultra-small chip size. In order for the target accelerator to support various neural network models, the neural network model can be converted into microcode through microcode compiler and mounted on accelerator to control the operators of the accelerator such as datapath and memory access. While the proposed controller and accelerator can run various CNN models, in this paper, we tested them using the YOLOv2-Tiny CNN model. Using a system clock of 200 MHz, the Controller and accelerator achieved an inference time of 137.9 ms/image for VOC 2012 dataset to detect object, 99.5ms/image for mask detection dataset to detect wearing mask. When implementing an accelerator equipped with the proposed controller as a silicon chip, the gate count is 618,388, which corresponds to 65.5% reduction in chip area compared with an accelerator employing a CPU-based controller (RISC-V).