Mel-cepstral methods for image feature extraction
Author
Çakır, Serdar
Çetin, A. Enis
Date
2010Source Title
2010 IEEE International Conference on Image Processing
Publisher
IEEE
Pages
4577 - 4580
Language
English
Type
Conference PaperItem Usage Stats
130
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Abstract
A 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.
Keywords
2D mel-cepstrumCepstral features
Face recognition
Image feature extraction
Cepstral
Cepstral analysis
Cepstral features
Cepstrum
Cepstrum method
Experimental studies
Face database
Feature extraction methods
Feature vectors
Fourier
Image feature extractions
Image matrix
Original images
ORL database
Recognition rates
Yale database
Database systems
Face recognition
Imaging systems
Speech recognition
Feature extraction
Permalink
http://hdl.handle.net/11693/28493Published Version (Please cite this version)
http://dx.doi.org/10.1109/ICIP.2010.5652293Collections
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