Browsing by Subject "Image feature extraction"

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    Mel-cepstral feature extraction methods for image representation
    (S P I E - International Society for Optical Engineering, 2010-15-09) Çakir, S.; Çetin, A. Enis
    An image feature extraction method based on the twodimensional (2-D) mel cepstrum is introduced. The concept of onedimensional mel cepstrum, which is widely used in speech recognition, is extended to 2-D in this article. The feature matrix resulting from the 2-D mel-cepstral analysis are applied to the support-vector-machine classifier with multi-class support to test the performance of the mel-cepstrum feature matrix. The AR, ORL, and Yale face databases are used in experimental studies, which indicate that recognition rates obtained by the 2-D mel-cepstrum method are superior to the recognition rates obtained using 2-D principal-component analysis and ordinary image-matrixbased face recognition. Experimental results show that 2-D mel-cepstral analysis can also be used in other image feature extraction problems. .
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    ItemOpen Access
    Mel-cepstral methods for image feature extraction
    (IEEE, 2010) Çakır, Serdar; Çetin, A. Enis
    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.