• Title/Summary/Keyword: 레이디얼 기저함수 신경망

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Face Recognition by Combining Linear Discriminant Analysis and Radial Basis Function Network Classifiers (선형판별법과 레이디얼 기저함수 신경망 결합에 의한 얼굴인식)

  • Oh Byung-Joo
    • The Journal of the Korea Contents Association
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    • v.5 no.6
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    • pp.41-48
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    • 2005

  • This paper presents a face recognition method based on the combination of well-known statistical representations of Principal Component Analysis(PCA), and Linear Discriminant Analysis(LDA) with Radial Basis Function Networks. The original face image is first processed by PCA to reduce the dimension, and thereby avoid the singularity of the within-class scatter matrix in LDA calculation. The result of PCA process is applied to LDA classifier. In the second approach, the LDA process Produce a discriminational features of the face image, which is taken as the input of the Radial Basis Function Network(RBFN). The proposed approaches has been tested on the ORL face database. The experimental results have been demonstrated, and the recognition rate of more than 93.5% has been achieved.

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