• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.1-15
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• 2005

As organizations search fur more secure authentication methods (Dr user access, e-commerce, and other security applications, biometrics is gaining increasing attention. Biometrics offers greater security and convenience than traditional methods of personal recognition. In some applications, biometrics can replace or supplement the existing technology. In others, it is the only viable approach. Several biometric methods of identification, including fingerprint hand geometry, facial, ear, iris, eye, signature and handwriting have been explored and compared in this paper. They all are well suited for the specific application to their domain. This paper briefly identifies and categorizes them in particular domain well suited for their application. Some methods are less intrusive than others.

• Environmental Analysis Health and Toxicology
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• v.23 no.1
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• pp.1-9
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• 2008

유산균인 비피도박테리아는 사람과 동물에서 유익한 프로바이오틱 미생물로 알려져 있다. 본 연구에서는 이러한 비피도박테리아 균주의 분류를 위한 repetitive DNA element PCR fingerprinting (ERIC-또는 TAP-PCR)의 사용을 평가하였다. 사람분변으로부터 분리한 알려지지 않은 비피도박테리움 균주와 한국생명공학연구원 생물자원센터로부터 분양받은 표준균주를 가지고 분류 및 동정에 ERIC-PCR과 TAP-PCR을 이용한 RAPD-fingerprinting을 수행하였다. 그 결과 비피도박테리움 균주에 대한 속과 종단위의 분류가 가능하였으며, 실험에 사용된 모든 비피도박테리움 균주는 RAPD-fingerprinting 분석을 통해 유전적 다양성을 확인하였다. 또한 ERIC2와 TAP1 프라이머를 이용한 실험에서는 Bifidobacterium adolescenits 특이 유전자 단편을 확인하였으며 이는 B. adolescenits 균주의 동정에 유용할 것으로 사료된다.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1157-1159
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• 1987

A syntactic and semantic approach is used to make type classification based on feature points(whorl, delta, core) and the shape of flow line around feature points. The image is divided into 30 by 30 subregions which are represented in the average direction and 4-tuple direction component. Next the relaxation process with singularity detection and convergency checking is performed. A set of semantic languages is used to describe the major flow line around the extracted feature points. LR(1) parser and feature transfer function are used to recognize the coded flow patterns. The 72 fingerprint impressions is used to test the proposed approach and the rate of the classification is about 93 percentages.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.1005-1010
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• 2012

We propose a novel approach to classify fingerprints using the extracted adaptive core block for improving classification performance of incomplete fingerprints in this paper. We compute representative directions from fingerprint images by the block unit and learn horizontal and vertical Markov models by deciding the center position of a fingerprint image based on the expert knowledge. The center block of a test image is the block has the highest probability after comparing the Markov model with $11{\times}11$ blocks. The proposed approach can effectively classify incomplete fingerprints using the optimal center block.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.139-142
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• 2001

컴퓨터 이미지처리는 여러 분야에서 응용되고 있는데 어떤 특성을 만족하는 객체들의 계수를 자동으로 분류시키는 생물학분야, 편지봉투나 일반양식에 인쇄되어 있는 글자를 자동으로 검출하고 인식하며 초음파검사 혹은 X-Ray 촬영에서 이미지를 획득하여 향상시키는 의료분야, 지문 및 얼굴인식 등에 이용되고 있다. 최근 몇 년 동안 이미지인식, 형태론, 이미지데이터 압축에 관한 연구가 진전되면서 본 연구에서 형태론적인 기법을 사용하여 문자인식을 위한 전처리 혹은 후처리 단계에서 사용되는 이미지향상을 위해서 침식, 골격화의 2단계를 적용하여 기종의 연구 방법과 비교하여 이미지획득 시간을 줄이고 이미지를 향상시켜 문자를 인식하는 알고리즘을 제안한다.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.173-178
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• 2008

Due to a rapid increase in demand for bigger-screen-equipped mobile phones in recent years, many big-name-manufactures have been releasing touch-screen-enabled devices. In this paper, various touch-screen-input methods have been summarized into 6 different categories. How? By tracing each user's finger print path, user's input pattern and behavior have been carefully recorded and analyzed. Through this analysis, what to be considered before designing UI is presented in great details.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.390-395
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• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.321-324
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• 2002

In this paper, we introduce a new approach to fingerprint classification based on both singular points and gabor features. We find singular points of fingerprint image by using squared direction field and Poincare index. Then, the input fingerprint image can be classified into one of 5 classes using the number of singular points and their location. However, it is often impossible to classify the fingerprint image because the numbers and the position of the singular points are not correct due to noise. In this case Gabor features are extracted from unclassified images using Gator filter and they are classified by using k-NN classifier. This method has been tested on the NIST-4 database. The experimental results show that the proposed method is reliable.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.407-429
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• 2004

As documents in webs are increasing explosively due to the rapid development of electronic documents, an efficient system classifying documents automatically is required. In this study, a new document classification method, which is called Document Finger Print Method, is suggested to classify web documents automatically and efficiently. The performance of the suggested method is evaluated alone with other existing methods such as key words based method, weighted key words based method, neural networks, and decision trees. An experiment is designed with 10 documents categories and 59 randomly selected words. The result shows that the suggested algorithm has a superior classifying performance compared to other methods. The most important advantage of this method is that the suggested method works well without the size limits of the number of words in documents.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.356-358
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• 2003

다중 사용자 환경에서 컴퓨터 시스템 보안을 위한 사용자 인증(user authentication)은 패스워드 (password), 토큰(token), 스마트 카드(smart card), 지문(fingerprint), 음성(voiceprint) 등 다양한 정보들을 통하여 시스템에 접근하는 사용자의 신원을 확인하고, 인증되지 않은 사용자의 접근을 제한한다. 이들 중 가장 보편적으로 사용되는 패스워드 기반 사용자 인증은 구현이 쉽고, 관리 비용이 적게 든다는 장점이 있다. 패스워드 기반 사용자 인증에서 패스워드의 선택은 시스템의 보안을 위하여 매우 중요하다. 따라서 시스템 관리 차원에서 사용자의 패스워드를 검사할 필요가 있다. 본 논문에서는 패스워드를 추측하기 쉬운 패스워드와 추측하기 어려운 패스워드로 분류하는 근거가 되는 여러 가지 패스워드들에 대한 특징들 중, 패스워드에 대한 언어적인 정보를 구별할 수 있는 특징을 제안한다. 또한 이를 신경망(neural network)을 사용하여 구현함으로써 보안 시스템의 특성에 따라 패스워드의 적합성 여부를 유연하게 조정할 수 있는 프로액티브 패스워드 체킹 방법을 제안한다.