”Small sample size”problem of LDA algorithm can be overcome by two—dimensional LDA f 2DLDA)，and Support Vector Machine(SVM)has the characteristic of structural risk minimization．In this paper，two methods were combined and used for face recognition．Firstly，the original images were decomposed into high—frequency and low—frequency components by Wavelet Transform(WT)．The high—frequency components were ignored，while the low—frequency components can be obtained．Then．the liner discriminant features were extracted by 2DLDA，and”one VS rest”。strategy of SVMs for muhiclass classification was chosen to perform face recognition． Experimental results based on ORL f Olivetti Research Laboratory1 face database and Yale face database show the validity of 2DLDA+SVM algorithm for face recogn ition．

2DLDAwiththeSVM-basedfacerecognitionalgorithm.PDF

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．