• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.1159-1162
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• 2005

휴대폰에 이용한 금융 활동이 늘어남에 따라 휴대폰 상에서의 보안의 필요성이 높아지게 되었다. 기존의 비밀번호 기반의 보안을 넘어 생체인식 기술이 휴대폰에 필요하게 되었다. 특히 홍채인식 기술이 지문인식이나 얼굴인식, 목소리 인식 등의 다른 생체인식 기술에 비해 신뢰성과 정확성 면에서 휴대폰에 적합한 기술이다. 본 논문에서는 휴대폰 환경에서 만족할 만한 성능과 처리시간을 보여주는 홍채인식 방법을 제안하고자 한다. 밝기와 대조를 조절하여 동공의 어두운 부분과 동공 반사광을 이용하여 홍채영역을 추출하는 방법을 제안한다. ARM 계열의 프로세서를 사용하는 휴대폰 프로세서의 특징에 맞도록 기존의 방법에서 사용되었던 실수 연산 방법을 줄여 처리 속도를 개선하였다. 실험 결과는 제안하는 방법의 휴대폰 환경에서 실시간으로 홍채인식을 수행하기에 적합한 성능을 보인다는 것을 보여준다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.619-621
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• 2002

생체인식은 중요한 보안기슬로 대두되고 있다. 특히 홍채인식은 보안에 있어서 특징의 유일성과 시간의 변화에 따른 안정성이라는 큰 장점을 가지고 있다. 홍채 인식율을 높이기 위해서는 특징 추출의 대상이 되는 영상이 중요하다. 또한 검증 시간의 단축을 꾀하기 위해서는 데이터 용량을 줄이기 위한 방법을 고려해야 한다. 이 두가지 문제를 해결하기 위하여 본 논문에서는 기존연구와 달리 홍채의 특징이 많이 분포되어 있는 영역을 찾아내어 홍채영상의 일부만을 특징추출의 대상으로 사용하고자 한다. 추출된 일부 홍채에 고차 국소 자기 상관함수를 적용하여 크기와 색상의 변화에 무관한 특징을 추출하고, 미리 학습된 신경망에서 홍채인식을 위한 최적의 신경망 구조를 찾아내어 인식율을 높이는 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.338-341
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• 2013

눈동자 검출은 운전 부주의 검출, 졸음 검출, 시선 검출 등 다양한 상황 인지에 이용되고 있다. 이러한 상황 인지를 위해 본 논문에서는 원 허프 변환(Hough Circle Transform)을 이용한 눈동자 검출방법을 제안한다. 이것은 영상 내 원을 검출하는 방법으로 연산량이 많아 실시간 처리에 문제가 된다. 이러한 문제를 해결하기 위해 눈 검출 후 눈 영역의 크기를 일정한 눈 크기로 정규화 하고 눈의 양쪽 끝점간 거리에 따른 대략적인 눈동자의 반지름 값 범위를 추정한다. 그 추정된 반지름 값 범위 내에서 Hough Circle Transform을 수행하면 연산량의 축소가 가능하며 그 결과 초당 21frames 정도의 눈동자 검출이 가능하였다.

• Journal of Environmental Impact Assessment
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• v.5 no.1
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• pp.107-121
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• 1996

The objective of this study is to establish the application method of environmental information system which is related to hazard identification for Health Risk Assessment. For establishing the environmental information system, fourteen hazardous chemicals were chosen and applicated to the database network such as RTKNET(Right Know Net), MSDS(Material Safety Data Sheets), TRI(Toxic Release Inventory), IRIS, AIRS, etc. The searching method of environmental information is classified to three sections such as the domestic commercial information company, international database agencies, and internet. Recently the importance of environmental information is being emphasized because it is essential 10 use database system in the field of environmental studies. Most of the foreign research organizations are communicating actively for information exchange, and the improvement of the quality of research. It is required to accumulate the data and develop them to database for future research.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.233-238
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• 2016

In this paper, we propose the algorithms of processing the uncertainty data using data fusion for the next generation intrusion detection. In the next generation intrusion detection, a lot of data are collected by many of network sensors to discover knowledge from generating information in cyber space. It is necessary the data fusion process to extract knowledge from collected sensors data. In this paper, we have proposed method to represent the uncertainty data, by classifying where is a confidence interval in interval of uncertainty data through feature analysis of different data using inference method with Dempster-Shafer Evidence Theory. In this paper, we have implemented a detection experiment that is classified by the confidence interval using IRIS plant Data Set for anomaly detection of uncertainty data. As a result, we found that it is possible to classify data by confidence interval.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.10
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• pp.1-11
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• 1993

A narrow-band dual TE$_{111}$ mode circular waveguide filter for Ku-Band satellite transponder was designed and manufactured based on a new model of the filter. We calculated the cavity size, pin polarizer depth and diameter, iris length and width, and used Bethe's Small Diffraction Theory and Chon's Correction Formular in order to obtain exact Result for each cavity. The designed dual model waveguide filter was manufactured with invar in order to maintain the thermal stability, and the filter performance was improved through the thermal test and vibration test to endure in the cosmic environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.61-64
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• 2011

There are many applications that require robust and accurate eye tracking, such as human-computer interface(HCI). In this paper, a novel approach for eye tracking with a principal component analysis on rotated face. In the process of iris detection, intensity information is used. First, for select eye region using principal component analysis. Finally, for eye detection using eye region's intensity. The experimental results show good performance in detecting eye from FERET image include rotate face.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2124-2139
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• 2023

In this article, the authors focus on the use of smart CCTV, a combnation of biometric recognition technology and AI algorithms. In fact, the advancements in relevant technologies brought a significant increase in the use of biometric information - fingerprint, retina, iris or facial recognition - across diverse sectors. Both the public and private sectors, with the developments of biometric technology, widely adopt and use an individual's biometric information for different reasons. For instance, smartphone users highly count on biometric technolgies for the purpose of security. Public and private orgazanitions control an access to confidential information-controlling facilities with biometric technology. Biometric infomration is known to be unique and immutable in the course of one's life. Given the uniquness and immutability, it turned out to be as reliable means for the purpose of authentication and verification. However, the use of biometric information comes with cost, posing a privacy issue. Once it is leaked, there is little chance to recover damages resulting from unauthorized uses. The governments across the country fully understand the threat to privacy rights with the use of biometric information and AI. The EU and the United States amended their data protection laws to regulate it. South Korea aligned with them. Yet, the authors point out that Korean data aprotection law still requires more improvements to minimize a concern over privacy rights arising from the wide use of biometric information. In particular, the authors stress that it is necessary to amend Section (2) of Article 23 of PIPA to reflect the concern by changing the basis for permitting the processing of sensitive information from 'the Statutes' to 'the Acts'.

• 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.