A new approach for fingerprint recognition based on mel frequency cepstral coefficients

This paper presents a new fingerprint identification method based on mel frequency cepstral coefficients (MFCCs). This method is based on the transformation of the fingerprint images into a 1-D signals and the extraction of the MFCCs from these signals. Feature matching is performed in the proposed...

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Bibliographic Details
Published in2009 International Conference on Computer Engineering & Systems pp. 263 - 268
Main Authors Hashad, F.G., Halim, T.M., Diab, S.M., Sallam, B.M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Discrete wavelet transforms
Feature extraction
Fingerprint recognition
Mel frequency cepstral coefficient
Neural networks
Noise reduction
Noise robustness
Signal processing
Speech enhancement
Wavelet transforms
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Summary:This paper presents a new fingerprint identification method based on mel frequency cepstral coefficients (MFCCs). This method is based on the transformation of the fingerprint images into a 1-D signals and the extraction of the MFCCs from these signals. Feature matching is performed in the proposed method using neural networks. Wavelet transform of the 1-D fingerprint signals can be used for extraction of much more MFCCs to assist in the recognition process. Also wavelet denoising can be used to reduce noise. Experimental results show that the proposed method is robust in the presence of noise.
ISBN:1424458420
9781424458424
DOI:10.1109/ICCES.2009.5383272