• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.968-976
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• 2014

Authentication methods on smartphone are demanded to be implicit to users with minimum users' interaction. Existing authentication methods (e.g. PINs, passwords, visual patterns, etc.) are not effectively considering remembrance and privacy issues. Behavioral biometrics such as keystroke dynamics and gait biometrics can be acquired easily and implicitly by using integrated sensors on smartphone. We propose a biometric model involving keystroke dynamics for implicit authentication on smartphone. We first design a feature extraction method for keystroke dynamics. And then, we build a fusion model of keystroke dynamics and gait to improve the authentication performance of single behavioral biometric on smartphone. We operate the fusion at both feature extraction level and matching score level. Experiment using linear Support Vector Machines (SVM) classifier reveals that the best results are achieved with score fusion: a recognition rate approximately 97.86% under identification mode and an error rate approximately 1.11% under authentication mode.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.133-139
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• 2014

Nowadays, telemedicine and remote prescription has been operating as a pilot basis. However, in case of remote hospitals without encrypting the biometric data transmission and its contents, the patient prescription data hacked from hackers who changed prescription medications can be serious obstacles to the patient. Therefore, in this paper, to solve this problem, password encryption, personal identification information, biometric data security on the patient's prescription and remote medical information system, and implementation of the encryption algorithm are proposed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.389-398
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• 2000

The popular methods to check the identity of individuals include passwords and ID cards. These conventional method for user identification and authentication are not altogether reliable because they can be stolen and forgotten. As an alternative of the existing methods, biometric technology has been paid much attention for the last few decades. In this paper, we propose an efficient system for recognizing the identity of a living person by analyzing iris patterns which have a high level of stability and distinctiveness than other biometric measurements. The proposed system is based on wavelet transform and a competitive neural network with the improved mechanisms. After preprocessing the iris data acquired through a CCD camera, feature vectors are extracted by using Haar wavelet transform. LVQ(Learning Vector Quantization) is exploited to classify these feature vectors. We improve the overall performance of the proposed system by optimizing the size of feature vectors and by introducing an efficient initialization of the weight vectors and a new method for determining the winner in order to increase the recognition accuracy of LVQ. From the experiments, we confirmed that the proposed system has a great potential of being applied to real applications in an efficient and effective way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2420-2433
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• 2014

Fusing the scores of multibiometrics is a very promising approach to improve the overall system's accuracy and the verification performance. In recent years, there are several approaches towards studying score level fusion of several biometric systems. However, most of them does not consider the genuine and imposter score distributions and result in a higher equal error rate usually. In this paper, a novel score level fusion approach of different biometric systems (dual iris, thermal and visible face traits) based on $Acz{\acute{e}}l$-Alsina triangular norm is proposed. It achieves higher identification performance as well as acquires a closer genuine distance and larger imposter distance. The experimental tests are conducted on a virtual multibiometrics database, which merges the challenging CASIA-Iris-Thousand database with noisy samples and the NVIE face database with visible and thermal face images. The rigorous results suggest that significant performance improvement can be achieved after the implementation of multibiometrics. The comparative experiments also ascertain that the proposed fusion approach outperforms the state-of-art verification performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.639-642
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• 2007

오늘날 네트워크의 급속한 발전에 더불어 정보화의 가속화는 보안 문제가 크게 부각하고 있다. 이에 마그네틱 카드, IC 카드 등을 이용하여 개인을 식별하는 다양한 보안 시스템들이 개발되고 있으나 분실, 복사, 고의적 양도에 의한 부정사용 등의 문제로 인해 그 해결책이 되지 않고 있으며 이에 대한 해결책으로 생체인식(Biometrics)을 이용한 개인식별 시스템[1]이 제안되어 연구가 진행되고 있다. 본 논문은 기존의 생체인식 시스템 중 가장 활발하게 활용되고 있는 지문인식 시스템이 가지고 있는 환경적인 요소나 물리적 요소에 의한 인식률 저하를 보안할 수 있는 시스템을 새롭게 제안한다. 지문인식은 사용의 편리함과 저가의 초기 투자비용, 그리고 소형화의 가능으로 생체인식 중에서 실생활에 사용되기 가장 적합한 기법으로 여겨져 다양한 응용 범위에 널려 사용되고 있다. 따라서, 제안 시스템은 기존의 지문인식 시스템을 기반으로 하여 손가락에서 추가적인 생체정보를 이용함으로써 지문인식 시스템이 갖은 단점을 보안하면서 인식률 향상과 효율적인 활용이 가능한 시스템을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5474-5490
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• 2017

Although two-dimensional principal component analysis (2DPCA) has been shown to be successful in face recognition system, it is still very sensitive to illumination variations. To reduce the effect of these variations, texture-based techniques are used due to their robustness to these variations. In this paper, we explore several texture-based techniques and determine the most appropriate one to be used with 2DPCA-based techniques for face recognition. We also propose a new distance metric computation in 2DPCA called Row Assembled Matrix Distance (RowAMD). Experiments on Yale Face Database, Extended Yale Face Database B, AR Database and LFW Database reveal that the proposed RowAMD distance computation method outperforms other conventional distance metrics when Local Line Binary Pattern (LLBP) and Multi-scale Block Local Binary Pattern (MB-LBP) are used for face authentication and face identification, respectively. In addition to this, the results also demonstrate the robustness of the proposed RowAMD with several texture-based techniques.

• Journal of fish pathology
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• v.34 no.2
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• pp.169-176
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• 2021

Parasitic infection is among the most common problems for carp cultivation. They are also important for the principal entrance of other hazardous infections as well. This study was carried out for determining of parasitic fauna of two major carp known as silver and grass carp with the comparison of prevalence value and intensity rate of parasites among them, alongside the relationship between the biometric characteristics and host sex with the infection level. For this purpose, a total of 94 fish samples were caught randomly using a fishing net, from Guilan ponds during spring and summer of the year 2018 and transported alive to the laboratory. Upon arriving, the biometric characteristics and genus of each carp were measured individually. Specimens were then acquired from the skin, gills, and eyes of the carp and examined according to standard parasitology methods. Recovered parasites were observed under a light microscope and then fixed for identification. As the result, the occurrence and intensity in the higher length group were comparatively greater than the lower one. Also, the prevalence and intensity of total parasites in male carp were higher than in females. In this research, Dactylogyrus hypophthalmichthys and Dactylogyrus aristhichtys were observed in silver carp and Dactylogyrus lamellatus was detected in grass carp. In the paper below, we found that the host specificity varies in different species of Dactylogyrus isolated from grass carp and silver carp.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.207-213
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• 2002

Fingerprint has the characteristics that do not change with time and is unique to an individual. And fingerprint identification is considered the best choice for most biometric applications because of its accuracy, speed, reliability, non-intrusive interfaces and cost-effectiveness. In this paper, we applies fingerprint Identification to web site login to raise the quality of personal identification when we use e-commerce, internet banking, stock dealings, shopping mali, etc. The system implemented in this paper consists of embedded module to carry out fingerprint identification, web server and web site. Existing system carries out fingerprint identification in the web server, but the system Implemented in this paper carries out it in client. Therefore the loads of server are reduced and the confidence of internet service is improved because login is forbidden without fingerprint identification success.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.156-163
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• 2004

In this paper, we propose an adaptive face region detection and real-time face identification algorithm using face feature evaluation function. The proposed algorithm can detect exact face region adaptively by using skin color information for races as well as intensity and elliptical masking method. And also, it improves face recognition efficiency using geometrical face feature and geometric evaluation function between features. The proposed algorithm can be used for the development of biometric and security system areas. In the experiment, the superiority of the proposed method has been tested using real image, the proposed algorithm shows more improved recognition efficiency as well as face region detection efficiency than conventional method.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.25-31
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• 2004

This paper is research about the improvement of recognition rate of the biometrics user identification system using the data previously stored in the non contact Ic smart card. The proposed system identifies the user by analyzing the iris pattern his or her us. First, after extracting the area of the iris from the image of the iris of an eye which is taken by CCD camera, and then we save PCA Coefficient using GHA(Generalized Hebbian Algorithm) into the Smart Card. When we confirmed the users, we compared the imformation of the biometrics of users with that of smart card. In case two kinds of information was the same, we classified the data by using SVM(Support Vector Machine). The Experimental result showed that this system outperformed the previous developed system.