• Title/Summary/Keyword: 퍼지 선형판별분석기법

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Iris Recognition using Gabor Wavelet and Fuzzy LDA Method (가버 웨이블릿과 퍼지 선형 판별분석 기법을 이용한 홍채 인식)

  • Go Hyoun-Joo;Kwon Mann-Jun;Chun Myung-Geun
    • Journal of KIISE:Software and Applications
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    • v.32 no.11
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    • pp.1147-1155
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    • 2005
  • This paper deals with Iris recognition as one of biometric techniques which is applied to identify a person using his/her behavior or congenital characteristics. The Iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D Iris pattern having a property of size invariant and using the fuzzy LDA which is further through four types of 2D Gabor wavelet. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use four different matching values obtained from four different directional Gabor wavelet and select the maximum value, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 300 Iris Patterns extracted from 50 subjects and finally got more higher than $90\%$ recognition rate.

An Emotion Recognition Method using Facial Expression and Speech Signal (얼굴표정과 음성을 이용한 감정인식)

  • 고현주;이대종;전명근
    • Journal of KIISE:Software and Applications
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    • v.31 no.6
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    • pp.799-807
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    • 2004
  • In this paper, we deal with an emotion recognition method using facial images and speech signal. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Emotion recognition using the facial expression is performed by using a multi-resolution analysis based on the discrete wavelet transform. And then, the feature vectors are extracted from the linear discriminant analysis method. On the other hand, the emotion recognition from speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and then the final recognition is obtained from a multi-decision making scheme.

Face Recognition using Fisherface Method with Fuzzy Membership Degree (퍼지 소속도를 갖는 Fisherface 방법을 이용한 얼굴인식)

  • 곽근창;고현주;전명근
    • Journal of KIISE:Software and Applications
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    • v.31 no.6
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    • pp.784-791
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    • 2004
  • In this study, we deal with face recognition using fuzzy-based Fisherface method. The well-known Fisherface method is more insensitive to large variation in light direction, face pose, and facial expression than Principal Component Analysis method. Usually, the various methods of face recognition including Fisherface method give equal importance in determining the face to be recognized, regardless of typicalness. The main point here is that the proposed method assigns a feature vector transformed by PCA to fuzzy membership rather than assigning the vector to particular class. In this method, fuzzy membership degrees are obtained from FKNN(Fuzzy K-Nearest Neighbor) initialization. Experimental results show better recognition performance than other methods for ORL and Yale face databases.

Multi-modal Biometrics System Based on Face and Signature by SVM Decision Rule (SVM 결정법칙에 의한 얼굴 및 서명기반 다중생체인식 시스템)

  • Min Jun-Oh;Lee Dae-Jong;Chun Myung-Geun
    • The KIPS Transactions:PartB
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    • v.11B no.7 s.96
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    • pp.885-892
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    • 2004
  • In this paper, we propose a multi-modal biometrics system based on face and signature recognition system. Here, the face recognition system is designed by fuzzy LDA, and the signature recognition system is implemented with the LDA and segment matching methods. To effectively aggregate two systems, we obtain statistical distribution models based on matching values for genuine and impostor, respectively. And then, the final verification is Performed by the support vector machine. From the various experiments, we find that the proposed method shows high recognition rates comparing with the conventional methods.

Face Recognition Under Ubiquitous Environments (유비쿼터스 환경을 이용한 얼굴인식)

  • Go, Hyoun-Joo;Kim, Hyung-Bae;Yang, Dong-Hwa;Park, Jang-Hwan;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.4
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    • pp.431-437
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    • 2004
  • This paper propose a facial recognition method based on an ubiquitous computing that is one of next generation intelligence technology fields. The facial images are acquired by a mobile device so-called cellular phone camera. We consider a mobile security using facial feature extraction and recognition process. Facial recognition is performed by the PCA and fuzzy LDA algorithm. Applying the discrete wavelet based on multi-resolution analysis, we compress the image data for mobile system environment. Euclidean metric is applied to measure the similarity among acquired features and then obtain the recognition rate. Finally we use the mobile equipment to show the efficiency of method. From various experiments, we find that our proposed method shows better results, even though the resolution of mobile camera is lower than conventional camera.