• The Magazine of the IEIE
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• v.33 no.3 s.262
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• pp.49-55
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• 2006

인간과 로봇의 자연스러운 상호작용을 위하여 영상과 음성을 기반으로 한 인간-로봇 상호작용 (HRI: Human Robot Interaction) 기술들을 소개한다. URC개념의 서버/클라이언트 구조를 갖는 소프트웨어 로봇에 수행 가능한 얼굴 인식 및 검증, 준 생체정보(semi biometrics)를 이용한 사용자 인식, 제스처인식, 화자인식 및 검증, 대화체 음성인식 기술들에 대하여 살펴본다. 이러한 인간-로봇 상호작용 기술들은 초고속 인터넷과 같은 IT 인프라를 이용하는 URC(Ubiquitous Robotic Companion) 기반의 지능형 서비스 로봇을 위한 핵심기술로서 사용되어진다.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.499-507
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• 2006

Recently human gait has been considered as a useful biometric supporting high performance human identification systems. This paper proposes a view-based pedestrian identification method using the dynamic silhouettes of a human body modeled with the Hidden Markov Model(HMM). Two types of gait models have been developed both with an endless cycle architecture: one is a discrete HMM method using a self-organizing map-based VQ codebook and the other is a continuous HMM method using feature vectors transformed into a PCA space. Experimental results showed a consistent performance trend over a range of model parameters and the recognition rate up to 88.1%. Compared with other methods, the proposed models and techniques are believed to have a sufficient potential for a successful application to gait recognition.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.381-384
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• 2004

오늘날 바이오 정보처리 소프트웨어의 품질은 각종 보안장치의 성능과 신뢰성을 좌우하는 중요한 요소로 자리잡고 있다. 국내의 경우, 아직 바이오 정보처리 소프트웨어에 대한 품질특성, 특히 신뢰성에 관한 품질평가와 인증이 자리잡지 못한 실정이며 평가와 인증을 위한 시험 인증체계가 구축되어 있지 않은 실정이다. 이로 인해, 바이오 정보처리 소프트웨어의 품질저하로 인한 생체인식 분야의 보안성 및 신뢰성 저하를 유발할 수 있는 문제점이 발생할 수 있다. 본 연구에서는 ISO/IEC 12119와 ISO/IEC 9126을 기반으로 바이오 정보처리 소프트웨어의 품질요구를 체계화하고 신뢰성 중심의 바이오 정보처리 소프트웨어 시험모듈과 시험모듈 적용을 위한 점검표를 구축하였다.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.395-396
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• 2019

최근 컴퓨터 하드웨어, 소프트웨어의 급속한 발전으로 상용화되면서 생체 인식 기술은 몇 년 전부터 점차 넓은 시장을 형성하고 있다. 본 논문에서는 얼굴 인식을 위하여 학습 데이터구성과 특징데이터에 따른 인식 정도를 파악하고 효과적인 방법으로 학습할 수 있는 방법을 제안하고자 한다. 실험결과, 원영상 그대로 인식하는 것 보다 특징 데이터를 구성하여 학습하는 것이 효율적임을 알 수 있다.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1233-1245
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• 2004

Though biometrics to authenticate a person is a good tool in terms of security and convenience, typical authentication algorithms using biometrics may not be executed on resource-constrained devices such as smart cards. Thus, to execute biometric processing on resource-constrained devices, it is desirable to develop lightweight authentication algorithm that requires only small amount of memory and computation. Also, among biological features, face is one of the most acceptable biometrics, because humans use it in their visual interactions and acquiring face images is non-intrusive. We present a new face authentication algorithm in this paper. Our achievement is two-fold. One is to present a face authentication algorithm with low memory requirement, which uses support vector machines (SVM) with the feature set extracted by genetic algorithms (GA). The other contribution is to suggest a method to reduce further, if needed, the amount of memory required in the authentication at the expense of verification rate by changing a controllable system parameter for a feature set size. Given a pre-defined amount of memory, this capability is quite effective to mount our algorithm on memory-constrained devices. The experimental results on various databases show that our face authentication algorithm with SVM whose input vectors consist of discriminating features extracted by GA has much better performance than the algorithm without feature selection process by GA has, in terms of accuracy and memory requirement. Experiment also shows that the number of the feature ttl be selected is controllable by a system parameter.

• Smart Media Journal
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• v.7 no.4
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• pp.90-98
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• 2018

A Multilinear LDA Method of Tensor Representation for ECG Signal Based Individual Identification Electrocardiogram signals, included in the cardiac electrical activity, are often analyzed and used for various purposes such as heart rate measurement, heartbeat rhythm test, heart abnormality diagnosis, emotion recognition and biometrics. The objective of this paper is to perform individual identification operation based on Multilinear Linear Discriminant Analysis (MLDA) with the tensor feature. The MLDA can solve dimensional aspects of classification problems in high-dimensional tensor, and correlated subspaces can be used to distinguish between different classes. In order to evaluate the performance, we used MPhysionet's MIT-BIH database. The experimental results on this database showed that the individual identification by MLDA outperformed that by PCA and LDA.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.667-680
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• 2007

The bio-data processing is used for a suitable purpose with bio-signals, which are obtained from human individuals. Recently, there is increasing demand that the bio-data has been widely applied to various applications. However, it is often that the number of data within each class is limited and the number of classes is large due to the property of problem domain. Therefore, the conventional pattern recognition systems and classification methods are suffering form low generalization performance because the system using the lack of data is influenced by noises of that. To solve this problem, we propose a modified additive factor model for bio-data generation, with two factors; the class factor which affects properties of each individuals and the environment factor such as noises which affects all classes. We then develop a classification system through defining a new similarity function using the proposed model. The proposed method maximizes to use an information of the class classification. So, we can expect to obtain good generalization performances with robust noises from small number of datas for bio-data. Experimental results show that proposed method outperforms significantly conventional method with real bio-data.

• Review of KIISC
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• v.22 no.4
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• pp.21-28
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• 2012

최근 스마트폰을 이용한 모바일 금융 서비스 시장이 증대되고 있으나 개방된 무선인터넷을 사용하며 도난 및 분실의 위험이 큰 모바일 환경의 특성으로 인하여 안전한 인증 기술의 필요성이 대두되고 있다. 최근 모든 플랫폼에서 사용할 수 있는 오픈 뱅킹에 대한 수요와 편의성에 대한 요구로 기존의 공개키 기반의 인증 방식인 공인인증서를 대체할 수 있는 새로운 인식 기술이 요구되고 있다. 사용자의 생체 특성을 이용하는 바이오 인식 기술은 모바일에 탑재되어 있는 기본입력 장치를 이용하여 바이오 정보를 인식하는 것이 가능하며 별도의 소지 없이 간단히 인식이 가능하기 때문에 모바일 지급 결제에 공인인증서를 대체할 수단으호 사용될 수 있다. 아직 모바일 지급결재에 바이오인식 기술을 적용하기에는 인식률의 정확도 향상이 필요한 상태이나 이를 위한 소프트웨어 및 하드웨어적인 개선이 이루어진다면 안전한 모바일 지급결제 환경을 구축할 수 있을 것으로 기대된다.

• Journal of KIISE:Software and Applications
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• v.37 no.11
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• pp.859-865
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• 2010

In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.