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A Novel Feature Extraction Algorithm from Fingerprint Image in Wavelet Domain

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Book cover Computational Intelligence, Cyber Security and Computational Models

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 412))

Abstract

The robustness of a fingerprint authentication system depends on the quality of the features extracted from the fingerprint image. For extracting good quality features, the quality of the image is to be improved through denoising and enhancement. In this paper, a set of invariant moment features are extracted from the approximation coefficient in the wavelet domain. Initially the fingerprint image is denoised using Stationary Wavelet Transform (SWT), a threshold based on Golden Ratio and weighted median. Then the denoised image is enhanced using Short Time Fourier Transform (STFT). A unique core point is then detected from the enhanced image by using complex filters to determine a Region of Interest (ROI), which is centered at the enhanced image. Then the ROI is decomposed using SWT at level one of Daubechies wavelet filter for extracting efficient features. The decomposed image is partitioned into four sub-images to reduce the effects of noise and nonlinear distortions. Finally a total of four sets of seven invariant moment features are extracted from four partitioned sub-images of an ROI of the approximation coefficient as it will contain low frequency components. To measure the similarity between feature vectors of an input fingerprint with the template stored in the database, the Euclidean Distance is employed for FVC2002 dataset. Using a simpler distance measure can substantially reduce the computational complexity of the system.

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Authors and Affiliations

  1. Department of Computer Science, Periyar University, Salem, India

    K. Sasirekha & K. Thangavel

Authors
  1. K. Sasirekha
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  2. K. Thangavel
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Corresponding author

Correspondence to K. Sasirekha .

Editor information

Editors and Affiliations

  1. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Muthukrishnan Senthilkumar

  2. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Vijayalakshmi Ramasamy

  3. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    Shina Sheen

  4. Applied Mathematics and Computational Sc, PSG College of Technology, Coimbatore, Tamil Nadu, India

    C. Veeramani

  5. Department of Mathematics, Ryerson University, TORONTO, Ontario, Canada

    Anthony Bonato

  6. Fac. Science&Technology, Deakin University, Burwood, Australia

    Lynn Batten

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Sasirekha, K., Thangavel, K. (2016). A Novel Feature Extraction Algorithm from Fingerprint Image in Wavelet Domain. In: Senthilkumar, M., Ramasamy, V., Sheen, S., Veeramani, C., Bonato, A., Batten, L. (eds) Computational Intelligence, Cyber Security and Computational Models. Advances in Intelligent Systems and Computing, vol 412. Springer, Singapore. https://doi.org/10.1007/978-981-10-0251-9_14

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  • DOI: https://doi.org/10.1007/978-981-10-0251-9_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0250-2

  • Online ISBN: 978-981-10-0251-9

  • eBook Packages: EngineeringEngineering (R0)

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