Browsing by Subject "Image matrix"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item Open Access Mel-cepstral methods for image feature extraction(IEEE, 2010) Çakır, Serdar; Çetin, A. EnisA 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.Item Open Access Two-dimensional Mellin and mel-cepstrum for image feature extraction(Springer, Dordrecht, 2010) Çakır, Serdar; Çetin, A. EnisAn image feature extraction method based on two-dimensional (2D)Mellin cepstrum is introduced. The concept of one-dimensional (1D) melcepstrum which is widely used in speech recognition is extended to two-dimensions both using the ordinary 2D Fourier Transform and the Mellin transform in this article. The resultant feature matrices are applied to two different classifiers (Common Matrix Approach and Support Vector Machine) to test the performance of the melcepstrum and Mellincepstrum based features. Experimental studies indicate that recognition rates obtained by the 2D melcepstrum based method are superior to the recognition rates obtained using 2D PCA and ordinary image matrix based face recognition in both classifiers. © 2011 Springer Science+Business Media B.V.