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Optical Engineering

Mel-cepstral feature extraction methods for image representation
Author(s): Serdar Cakir; A. Enis Cetin
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Paper Abstract

An image feature extraction method based on the two-dimensional (2-D) mel cepstrum is introduced. The concept of one-dimensional 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-matrix-based face recognition. Experimental results show that 2-D mel-cepstral analysis can also be used in other image feature extraction problems.

Paper Details

Date Published: 1 September 2010
PDF: 8 pages
Opt. Eng. 49(9) 097004 doi: 10.1117/1.3488050
Published in: Optical Engineering Volume 49, Issue 9
Show Author Affiliations
Serdar Cakir, Bilkent Univ. (Turkey)
A. Enis Cetin, Bilkent Univ. (Turkey)

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