• Journal of KIISE
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• v.42 no.4
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• pp.419-426
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• 2015

This paper proposes a fingerprint verification system on a fuzzy vault with steganography for a smartphone. While biometric-based authentication can provide strong security, the biometric data must be handled carefully as it cannot be re-enrolled when it is revealed to other people. When the transformed data is used for authentication, the original biometric data can be protected. In this paper, we combine a fingerprint verification system with a fuzzy vault scheme to protect the fingerprint data of a smartphone user. In addition, the transformed data using a fuzzy vault scheme increases the security as it is concealed by the steganography scheme. The result of the experiment using fingerprint databases shows that the proposed scheme provides a high level of convenience and security for authentication of a smartphone having with a fingerprint sensor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.734-739
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• 2018

Fingerprint recognition and iris recognition, which are one of the biometric methods, are easily influenced by external factors such as sunlight. Recently, finger vein recognition is used as a method utilizing internal features. However, for accurate finger vein recognition, it is important to clearly separate vein and background regions. However, it is difficult to separate the vein region and background region due to the abnormalized illumination, and a method of separating the vein region and the background region after normalized the illumination of the input image has been proposed. In this paper, we proposed a method to enhance the quality improvement and improve the processing time compared to the existing finger vein recognition system binarization and labeling method of the image including the image stretching process based on the existing illumination normalization method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6133-6151
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• 2017

The field of periocular biometrics has gained wide attention as an alternative or supplemental means to conventional biometric traits such as the iris or the face. Periocular biometrics provide intermediate resolution between the iris and the face, which enables it to support both. We have developed a periocular recognition system by using uniform Multiscale Local Binary Pattern (uMLBP) and attribute features. The proposed system has been evaluated in terms of major factors that need to be considered on a mobile platform (e.g., distance and facial pose) to assess the feasibility of the use of periocular biometrics on mobile devices. Experimental results showed 98.7% of rank-1 identification accuracy on a subset of the Face Recognition Grand Challenge (FRGC) database, which is the best performance among similar studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.166-183
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• 2013

It requires a lot of costs and manpower to manage an election. The electronic voting scheme can make the election system economic and trustful. The widespread use of smart phones causes mobile voting to be a major issue. The smart phone can be used as a mobile voting platform since it can carry out many services in addition to basic telephone service. To make mobile voting practical and trustful, we analyzed two subjects of study. Firstly, the way to make a biometric based mobile ID, which has legal binding forces. In mobile voting, user identification is accomplished on line since the voter should be able to vote wherever they go. The digital ID conducts a similar role to the need for a resident card. The user's identity is bound to the resident card legally. To bind the user's identity to the smart phone, we use USIM. Biometric recognition is also needed to authenticate the user, since the user cannot prove him or her on line face-to-face. The proposed mobile ID can be reissued by means of introducing a random secret value. Secondly, the mobile voting scheme is proposed where candidates can accept election results without doubt. The goal of an election is to select a leader among two or more candidates. Existing electronic voting schemes mainly focus on the study of ballot verification accomplished by voters. These approaches are not safe against collusion attacks where candidates and the election administration center are able to collude to fabricate election results. Therefore, a new type of voting and counting method is needed where candidates can directly take part in voting and counting stages. The biometric based multi-signature scheme is used to make the undeniable multi-signed ballot. The ballot cannot be verified without the help of all candidates. If candidates accept election results without a doubt, the fairness of the election is satisfied.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.106-109
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• 2003

Many diverse methods have been developing in the field of biometric identification as human-friendliness has been emphasized in the intelligent system's area. One of emerging method is to use human footprint. Automated footprint-based person recognition was started by Nakajima et al.'s research but they showed relatively low recognition result by low spatial resolution of pressure sensor and standing posture. In this paper, we proposed a modified Nakajima's method to use walking footprint which could give more stable toe information than standing posture. Finally, we prove the usefulness of proposed method as 91.4tt recognition rate in 11 volunteers' test.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.445-458
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• 2012

Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.

• Korean Journal of Artificial Intelligence
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• v.5 no.2
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• pp.15-25
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• 2017

Recently, technologies are being developed to recognize and authenticate users using bioinformatics to solve information security issues. Biometric information includes face, fingerprint, iris, voice, and vein. Among them, face recognition technology occupies a large part. Face recognition technology is applied in various fields. For example, it can be used for identity verification, such as a personal identification card, passport, credit card, security system, and personnel data. In addition, it can be used for security, including crime suspect search, unsafe zone monitoring, vehicle tracking crime.In this thesis, we conducted a study to recognize faces by detecting the areas of the face through a computer webcam. The purpose of this study was to contribute to the improvement in the accuracy of Recognition of Face Based on CNN Algorithms. For this purpose, We used data files provided by github to build a face recognition model. We also created data using CNN algorithms, which are widely used for image recognition. Various photos were learned by CNN algorithm. The study found that the accuracy of face recognition based on CNN algorithms was 77%. Based on the results of the study, We carried out recognition of the face according to the distance. Research findings may be useful if face recognition is required in a variety of situations. Research based on this study is also expected to improve the accuracy of face recognition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.175-181
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• 2009

In this paper, we introduce the implementation of the security system using iris recognition. This system acquires images with infrared camera and extracts the 2D code from a infrared image which uses scale-space filtering and concavity. We examine the system by (i) extract 2D code and (ii) compare the code that stored on the server (iii) mearsure FAR and FRR using pattern matching. Experiment results show that the proposed method is very suitable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.107-112
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• 2011

In this paper, we introduce the implementation of the security system using iris recognition. This system acquires images with infrared camera and extracts the 2D code from a infrared image which uses scale-space filtering and concavity. We examine the system by (i) extract 2D code and (ii) compare the code that stored on the server (iii) measure FAR and FRR using pattern matching. Experiment results show that the proposed method is very suitable.