Mel-cepstral methods for image feature extraction

buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage4580en_US
dc.citation.spage4577en_US
dc.contributor.authorÇakır, Serdaren_US
dc.contributor.authorÇetin, A. Enisen_US
dc.coverage.spatialHong Kong, Chinaen_US
dc.date.accessioned2016-02-08T12:22:06Z
dc.date.available2016-02-08T12:22:06Z
dc.date.issued2010en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 26-29 Sept. 2010en_US
dc.description.abstractA 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.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T12:22:06Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2010en
dc.identifier.doi10.1109/ICIP.2010.5652293en_US
dc.identifier.urihttp://hdl.handle.net/11693/28493
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICIP.2010.5652293en_US
dc.source.title2010 IEEE International Conference on Image Processingen_US
dc.subject2D mel-cepstrumen_US
dc.subjectCepstral featuresen_US
dc.subjectFace recognitionen_US
dc.subjectImage feature extractionen_US
dc.subjectCepstralen_US
dc.subjectCepstral analysisen_US
dc.subjectCepstral featuresen_US
dc.subjectCepstrumen_US
dc.subjectCepstrum methoden_US
dc.subjectExperimental studiesen_US
dc.subjectFace databaseen_US
dc.subjectFeature extraction methodsen_US
dc.subjectFeature vectorsen_US
dc.subjectFourieren_US
dc.subjectImage feature extractionsen_US
dc.subjectImage matrixen_US
dc.subjectOriginal imagesen_US
dc.subjectORL databaseen_US
dc.subjectRecognition ratesen_US
dc.subjectYale databaseen_US
dc.subjectDatabase systemsen_US
dc.subjectFace recognitionen_US
dc.subjectImaging systemsen_US
dc.subjectSpeech recognitionen_US
dc.subjectFeature extractionen_US
dc.titleMel-cepstral methods for image feature extractionen_US
dc.typeConference Paperen_US

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