• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.10-18
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• 2019

Since the introduction of CRT(Cathode Ray Tube) in the 1950s, display technologies have been developed continuously. Flat panel displays such as PDP(Plasma Display Panel) and LCD(Liquid Crystal Display) were commercialized in the late 1990s, and OLED(Organic Light Emitting Diodes) and Micro-LED(Micro-Light Emitting Diodes) are now being developed and are becoming widespread. In the future, we expect to develop ultra-realistic, flexible, embedded sensor displays. Ultra-realistic display can be applied to AR/VR(Augmented Reality/Virtual Reality) devices and spatial light modulators for holography. The sensor-embedded display can be applied to robots; electronic skin; and security devices, including iris recognition sensors, fingerprint recognition sensors, and tactile sensors. AR/VR technology must be developed to meet technical requirements such as viewing angle, resolution, and refresh rate. Holography requires optical modulation technology that can significantly improve resolution, viewing angle, and modulation method to enable wide-view and high-quality hologram stereoscopic images. For electronic skin, stable mass production technology, large-area arrays, and system integration technologies should be developed.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.465-471
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• 2018

Recently, biometric technology has begun to be used as a fusion of IT technology and financial system. Using this biometric technology, FIDO(Fast Identity Online) technology, Samsung and Apple started Samsung Pay and Apple Pay service. FIDO authentication technology replaces existing authentication methods such as passwords. Among the biometric technologies, fingerprint recognition technology is attracting attention because it can minimize the device and user rejection at a relatively low price. However, fingerprint information has a limited number of users and it can not be reused if fingerprint information is leaked by an external attacker. Therefore, in this paper, we propose a method to authenticate a user using EEG signal which is one of biometrics technologies. W propose a method to use EEG signal measurement value in FIDO system by using convenience channel by using short channel EEG device. And propose a method to utilize EEG signal when the user recognizes a specific entity by measuring the EEG signal before and after recognizing a specific entity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.33-38
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• 2008

Biometric based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as compromise of the data will be permanent. Cancelable biometrics stores a non - invertible transformed version of the biometric data. Thus, even if the storage is compromised, the biometric data remains safe. Cancelable biometrics also provide a higher level of privacy by allowing many templates for the same biometric data and hence non-linkability of user's data stored in different databases. In this paper, we proposed the fast polynomial reconstruction algorithm for fuzzy fingerprint vault. The proposed method needs (k+1) real points to reconstruct the polynomial of degree (k-1). It enhances the speed, however, by $300{\sim}1500$ times according to the degree of polynomial compared with the exhaust search.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.343-348
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• 2014

Face recognition system has advanctage to automatically recognize a person without causing repulsion at deteciton process. However, the face recognition system has a drawback to show lower perfomance according to illumination variation unlike the other biometric systems using fingerprint and iris. Therefore, this paper proposed a robust face recogntion method against illumination varition by slective fusion technique using both visible and infrared faces based on fuzzy linear disciment analysis(fuzzy-LDA). In the first step, both the visible image and infrared image are divided into four bands using wavelet transform. In the second step, Euclidean distance is calculated at each subband. In the third step, recognition rate is determined at each subband using the Euclidean distance calculated in the second step. And then, weights are determined by considering the recognition rate of each band. Finally, a fusion face recognition is performed and robust recognition results are obtained.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.898-905
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• 2005

Iris recognition Is that identifies a user based on the unique iris muscle patterns which has the functionalities of dilating or contracting pupil region. Because it is reported that iris recognition is more accurate than other biometries such as face, fingerprint, vein and speaker recognition, iris recognition is widely used in the high security application domain. However, if unnecessary information such as eyelid and eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate iris code including eyelash and eyelid, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelid by using pyramid searching parabolic deformable template. In addition, we detect the eyelash by using the eyelash mask. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.3\%$ compared to that not using it.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2067-2073
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• 2001

Biometric systems are forms of technology that use unique human physical characteristics to automatically identify a person. They have sensors to pick up some physical characteristics, convert them into digital patterns, and compare them with patterns stored for individual identification. However, lip-print recognition has been less developed than recognition of other human physical attributes such as the fingerprint, voice patterns, retinal at blood vessel patterns, or the face. The lip print recognition by a CCD camera has the merit of being linked with other recognition systems such as the retinal/iris eye and the face. A new method using multi-resolution architecture is proposed to recognize a lip print from the pattern kernels. A set of pattern kernels is a function of some local lip print masks. This function converts the information from a lip print into digital data. Recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. The multi-resolution architecture allows us to reduce the false recognition rate from 15% to 4.7%. This paper shows that a lip print is sufficiently used by the measurements of biometric systems.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.764-772
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• 2001

This paper describes fingerprint matching algorithm using connected information between minutiae. We regard minutiae as ridge bifurcation and ridge ending. Features are composed of minutia's position, type(ridge bifurcation or ridge ending) ridge direction and connected ridge information. While the minutiae are extracted, we store connected in information between minutiae on the same ridge. They are used to find corresponding point pairs. Minutiae are aligned completely by two corresponding point pairs and point pattern matching is achieved by counting the number of overlapping pairs. It is invariable t translation and rotation. We have tested proposed method on the 445 fingerprints from 89 persons. These experimental results show that proposed algorithm improve 33% in speed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.553-559
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• 2004

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.10-20
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• 2002

The purpose of this work is to develop a system fer rapid and automatic identification of persons, with high reliability and confidence levels. The iris of the eye is used as an optical fingerprint, having a highly detailed pattern that is unique for each individual and stable over many years. Image analysis algorithms find the iris in a image, and encode its texture into an iris code. Iris texture is extracted from the image at multiple scales of analysis by wavelet transformation. The features of many different parts of the iris are projected onto the space-frequency space. They are used to determine an abstract iris code which is similar to 2D barcode. Pattern recognition is achieved by using modified CPN.