Two-dimensional Mellin and mel-cepstrum for image feature extraction
buir.contributor.author | Çetin, A. Enis | |
buir.contributor.orcid | Çetin, A. Enis|0000-0002-3449-1958 | |
dc.citation.epage | 276 | en_US |
dc.citation.spage | 271 | en_US |
dc.citation.volumeNumber | 62 | en_US |
dc.contributor.author | Çakır, Serdar | en_US |
dc.contributor.author | Çetin, A. Enis | en_US |
dc.date.accessioned | 2016-02-08T12:22:54Z | |
dc.date.available | 2016-02-08T12:22:54Z | |
dc.date.issued | 2010 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description | Conference name: Proceedings of the 25th International Symposium on Computer and Information Sciences | en_US |
dc.description.abstract | An 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. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T12:22:54Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2010 | en |
dc.identifier.doi | 10.1007/978-90-481-9794-1_52 | en_US |
dc.identifier.doi | 10.1007/978-90-481-9794-1 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/28523 | |
dc.language.iso | English | en_US |
dc.publisher | Springer, Dordrecht | en_US |
dc.relation.isversionof | https://doi.org/10.1007/978-90-481-9794-1_52 | en_US |
dc.relation.isversionof | https://doi.org/10.1007/978-90-481-9794-1 | en_US |
dc.source.title | Computer and Information Sciences | en_US |
dc.subject | Cepstrum | en_US |
dc.subject | Experimental studies | en_US |
dc.subject | Image feature extractions | en_US |
dc.subject | Image matrix | en_US |
dc.subject | Matrix approach | en_US |
dc.subject | Mellin transform | en_US |
dc.subject | Recognition rates | en_US |
dc.subject | Classifiers | en_US |
dc.subject | Face recognition | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Fourier transforms | en_US |
dc.subject | Information science | en_US |
dc.subject | Two dimensional | en_US |
dc.subject | Speech recognition | en_US |
dc.title | Two-dimensional Mellin and mel-cepstrum for image feature extraction | en_US |
dc.type | Conference Paper | en_US |
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