Wavelet packet correlation methods in biometrics.

Pablo Hennings; Jason Thornton; Jelena Kovacević; B V K Vijaya Kumar

doi:10.1364/ao.44.000637

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PubMed · 15751845

Wavelet packet correlation methods in biometrics.

Pablo Hennings·Jason Thornton·Jelena Kovacević·B V K Vijaya Kumar

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Abstract

We introduce wavelet packet correlation filter classifiers. Correlation filters are traditionally designed in the image domain by minimization of some criterion function of the image training set. Instead, we perform classification in wavelet spaces that have training set representations that provide better solutions to the optimization problem in the filter design. We propose a pruning algorithm to find these wavelet spaces by using a correlation energy cost function, and we describe a match score fusion algorithm for applying the filters trained across the packet tree. The proposed classification algorithm is suitable for any object-recognition task. We present results by implementing a biometric recognition system that uses the NIST 24 fingerprint database, and show that applying correlation filters in the wavelet domain results in considerable improvement of the standard correlation filter algorithm.

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Algorithms Artificial Intelligence Biometry Dermatoglyphics Image Enhancement Image Interpretation, Computer-Assisted Information Storage and Retrieval Numerical Analysis, Computer-Assisted Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Statistics as Topic Comparative Study Evaluation Study Journal Article

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Pablo Hennings, Jason Thornton, Jelena Kovacević, B V K Vijaya Kumar. 2005-02-10. Wavelet packet correlation methods in biometrics.. https://doi.org/10.1364/ao.44.000637

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