Çakır, SerdarÇetin, A. Enis2016-02-082016-02-082010http://hdl.handle.net/11693/28493Date of Conference: 26-29 Sept. 2010A 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.English2D mel-cepstrumCepstral featuresFace recognitionImage feature extractionCepstralCepstral analysisCepstral featuresCepstrumCepstrum methodExperimental studiesFace databaseFeature extraction methodsFeature vectorsFourierImage feature extractionsImage matrixOriginal imagesORL databaseRecognition ratesYale databaseDatabase systemsFace recognitionImaging systemsSpeech recognitionFeature extractionConference Paper10.1109/ICIP.2010.5652293