Mel-cepstral feature extraction methods for image representation

Serdar Cakir; A. Enis Cetin

doi:10.1117/1.3488050

1 September 2010 Mel-cepstral feature extraction methods for image representation

Serdar Cakir, A. Enis Cetin

Author Affiliations +

Optical Engineering, Vol. 49, Issue 9, 097004 (September 2010). https://doi.org/10.1117/1.3488050

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.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Serdar Cakir and A. Enis Cetin "Mel-cepstral feature extraction methods for image representation," Optical Engineering 49(9), 097004 (1 September 2010). https://doi.org/10.1117/1.3488050

Published: 1 September 2010

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