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      Mel-cepstral methods for image feature extraction

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      Author
      Çakır, Serdar
      Çetin, A. Enis
      Date
      2010
      Source Title
      2010 IEEE International Conference on Image Processing
      Publisher
      IEEE
      Pages
      4577 - 4580
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      A feature extraction method based on two-dimensional (2D) mel-cepstrum is introduced. The concept of one-dimensional (1D) mel-cepstrum which is widely used in speech recognition is extended to 2D in this article. Feature matrices resulting from the 2D mel-cepstrum, Fourier LDA, 2D PCA and original image matrices are converted to feature vectors and individually applied to a Support Vector Machine (SVM) classification engine for comparison. The AR face database, ORL database, Yale database and FRGC version 2 database are used in experimental studies, which indicate that recognition rates obtained by the 2D mel-cepstrum method is superior to the recognition rates obtained using Fourier LDA, 2D PCA and ordinary image matrix based face recognition. This indicates that 2D mel-cepstral analysis can be used in image feature extraction problems. © 2010 IEEE.
      Keywords
      2D mel-cepstrum
      Cepstral features
      Face recognition
      Image feature extraction
      Cepstral
      Cepstral analysis
      Cepstral features
      Cepstrum
      Cepstrum method
      Experimental studies
      Face database
      Feature extraction methods
      Feature vectors
      Fourier
      Image feature extractions
      Image matrix
      Original images
      ORL database
      Recognition rates
      Yale database
      Database systems
      Face recognition
      Imaging systems
      Speech recognition
      Feature extraction
      Permalink
      http://hdl.handle.net/11693/28493
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/ICIP.2010.5652293
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      • Department of Electrical and Electronics Engineering 3597
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