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A Fingerprint Enhancement Algorithm in Spatial and Wavelet Domain

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Advances in Internet, Data & Web Technologies (EIDWT 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 17))

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Abstract

Fingerprinting is one form of biometrics, which people’s physical characteristics to identify them. Fingerprints are ideal for this purpose because they’re inexpensive to be collected and analysed. They never change, even as people grow old. The performance of a fingerprint image-matching algorithm depends heavily on the quality of the input fingerprint images. The acquired fingerprint images from the scanner are often with low contrast, noisy and the ridges are blurred. The enhancement is an essential step required to improve the quality of the fingerprint image. In this paper, we propose an enhancement method in spatial and wavelet domain. The fingerprint image contrast is increased, the histogram is equalized and ridges are deblurred. The image is then filtered by Gabor filters and denoised in wavelet domain. Experimental results show that this method increases the number of true minutiae extracted.

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Author information

Authors and Affiliations

  1. Polytechnic University of Tirana, Tirana, Albania

    Indrit Enesi, Algenti Lala & Elma Zanaj

Authors
  1. Indrit Enesi
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  2. Algenti Lala
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  3. Elma Zanaj
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Corresponding author

Correspondence to Indrit Enesi .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka-shi, Japan

    Leonard Barolli

  2. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  3. Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan

    Nadeem Javaid

  4. Polytechnic University of Tirana, Tirana, Albania

    Evjola Spaho

  5. Polytechnic University of Tirana, Tirana, Albania

    Vladi Kolici

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Enesi, I., Lala, A., Zanaj, E. (2018). A Fingerprint Enhancement Algorithm in Spatial and Wavelet Domain. In: Barolli, L., Xhafa, F., Javaid, N., Spaho, E., Kolici, V. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-75928-9_66

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  • DOI: https://doi.org/10.1007/978-3-319-75928-9_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75927-2

  • Online ISBN: 978-3-319-75928-9

  • eBook Packages: EngineeringEngineering (R0)

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