• 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.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.13-21
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• 2009

This paper describes research of image enhancement for detection of face area. Typical face recognition algorithms used fixed parameter filtering algorithms to optimize face images for the recognition process. A fixed filtering scheme introduces errors when applied to face images captured in various different environmental conditions. For acquiring face image of good quality from the image including complex background and illumination, we propose a method for image enhancement using the categories based on the image intensity values. When an image is acquired average values of image from sub-window are computed and then compared to training values that were computed during preprocessing. The category is selected and the most suitable image filter method is applied to the image. We used histogram equalization, and gamma correction filters with two different parameters, and then used the most suitable filter among those three. An increase in enrollment of filtered images was observed compared to enrollment rates of the original images.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.331-332
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• 2006

To enhance security and privacy in biometrics, changeable (or cancelable) biometrics have recently been introduced. The idea is to transform a biometric signal or feature into a new one for enrollment and matching. In this paper, we proposed changeable biometrics for face recognition using on PCA based approach. PCA coefficient vector extracted from an input face image. The vector is scrambled randomly and removed. When a transformed template is compromised, it is replaced by a new scrambling rule. In our experiment, we compared the performance between when PCA coefficient vectors are used for verification and when the transformed coefficient vectors are used for verification.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.15-18
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• 2007

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e. both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion is considered at decision level. The proposed algorithm is tested on the NLPR database.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.16-23
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• 2007

Changeable biometrics has been developed as a solution to problem of enhancing security and privacy. The idea is to transform a biometric signal or feature into a new one for the purposes of enrollment and matching. In this paper, we propose a changeable biometric system that can be applied to appearance based face recognition system. In the first step when using feature extraction, ICA(Independent Component Analysis) coefficient vectors extracted from an input face image are replaced randomly using their mean and variation. The transformed vectors by replacement are scrambled randomly and a new transformed face coefficient vector (transformed template) is generated by combination of the two transformed vectors. When this transformed template is compromised, it is replaced with new random numbers and a new scrambling rule. Because e transformed template is generated by e addition of two vectors, e original ICA coefficients could not be easily recovered from the transformed coefficients.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.649-654
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• 2005

In this paper, we describe an implementation of real-time face recognition system under ubiquitous computing environments. First, face image is captured by PDA with CMOS camera and then this image with user n and name is transmitted via WLAN(Wireless LAN) to the server and finally PDA receives verification result from the server The proposed system consists of server and client parts. Server uses PCA and LDA algorithm which calculates eigenvector and eigenvalue matrices using the face images from the PDA at enrollment process. And then, it sends recognition result using Euclidean distance at verification process. Here, captured image is first compressed by the wave- let transform and sent as JPG format for real-time processing. Implemented system makes an improvement of the speed and performance by comparing Euclidean distance with previously calculated eigenvector and eignevalue matrices in the learning process.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.72-77
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• 2008

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion in considered at decision level. The proposed algorithm is tested on the NLPR database.

• MALSORI
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• no.66
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• pp.105-116
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• 2008

In this research, we propose a speaker identification system using a kernel method which is expected to model the non-linearity of speech features well. We have been using principal component analysis (PCA) successfully, and extended to kernel PCA, which is used for many pattern recognition tasks such as face recognition. However, we cannot use kernel PCA for speaker identification directly because the storage required for the kernel matrix grows quadratically, and the computational cost grows linearly (computing eigenvector of $l{\times}l$ matrix) with the number of training vectors I. Therefore, we use greedy kernel PCA which can approximate kernel PCA with small representation error. In the experiments, we compare the accuracy of the greedy kernel PCA with the baseline Gaussian mixture models using MFCCs and PCA. As the results with limited enrollment data show, the greedy kernel PCA outperforms conventional methods.

• Korean Journal of Comparative Education
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• v.26 no.4
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• pp.1-30
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• 2016

The purposes of this study are to analyze the higher education admission policy of France and to draw policy implications for Korea. For this study, literature reviews and interviews (face-to-face, email, telephone) were adopted for main research methods. The major findings were as follows: First, baccalaur?at diploma is necessary for higher education admission in France but each higher education has different admission policy according to their legal status. University has open enrollment policy and has no student selection process. Other higher institutions such as grands ?coles select students based on students' academic achievements. Second, baccalaur?at is national diploma which shows successful conclusion of the upper secondary education and gives right of access to higher education. This diploma is awarded to candidates who have passed a series of standardized written and oral tests drawn up at national level (10/20points). Third, students' academic achievements in high schools are major criteria for admission for higher institutions which has student selection process. Fourth, entrance exams implemented at college level are various according to higher institution. Last, 'Admission Post-bac-APB' site is used to support and facilitate the whole admission process. Based on these findings, several policy implications were suggested.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.409-414
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• 2013

The purpose of this study is to verify the effects of partial-cyber and full-cyber lectures and explore directions for improvement. This study compared the mean scores of course evaluation for traditional face-to-face lectures, partial-cyber lectures of blended instruction, and full-cyber lectures. Also, this study interviewed instructors of full-cyber lectures to investigate the ways to enhance the lecture quality. The findings suggest that the course evaluation scores for full-cyber university were consistently lower than those for other types of lectures for four semesters between the years of 2011 and 2012. Results also showed that mean scores of partial-cyber lectures were the same as those of face-to-face lectures. After all, class satisfaction in full-cyber courses that learning occurs in cyber space was the lowest. Instructors who taught full-cyber lectures proposed that enrollment should not be within 60 students and professional assistance should be provided for lectures exceeding 60 students. Finally, they suggested content updates through a collaborative system with professionals, instructors' efforts to enhance interaction in both online and offline contexts, and learning quantity rationalization.