Comparison of MFCC and Cepstral Coefficients as a Feature Set for PCG Biometric Systems

Heart sound is an acoustic signal and many techniques used nowadays for human recognition tasks borrow speech recognition techniques. One popular choice for feature extraction of accoustic signals is the Mel Frequency Cepstral Coefficients (MFCC) which maps the signal onto a non-linear Mel-Scale that mimics the human hearing. However the Mel-Scale is almost linear in the frequency region of heart sounds and thus should produce similar results with the standard cepstral coefficients (CC). In this paper, MFCC is investigated to see if it produces superior results for PCG based human identification system compared to CC. Results show that the MFCC system is still superior to CC despite linear filter-banks in the lower frequency range, giving up to 95% correct recognition rate for MFCC and 90% for CC. Further experiments show that the high recognition rate is due to the implementation of filter-banks and not from Mel-Scaling.

Authors:

• Justin Leo Cheang Loong
• Khazaimatol S Subari
• Muhammad Kamil Abdullah
• Nurul Nadia Ahmad
• RosliBesar

Keywords:

• Biometric
• Phonocardiogram
• Cepstral Coefficients
• Mel Frequency

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