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Adaptive Fingerprint Enhancement by Combination of Quality Factor and Quantitative Filters

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Advances in Biometric Person Authentication (IWBRS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3781))

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Abstract

Fingerprint enhancement is a crucial step in automatic fingerprint recognition system, undiscriminating repeated filtering easily lead to false structure in low-quality regions of a fingerprint image. This paper presents a new adaptive enhancement algorithm that can automatically adjust the parameters of filters and the time of filtering according to the quality factors in different regions. In order to improve filtering efficiency, a template bank of 4-dimenstion scaleable array is also designed to quantize the filter and forms the basis of a new fused filter. Experimental results in eight low-quality images from FVC2004 data sets show that the proposed algorithm is higher 23.7% in Good Index (GI), and saves 54.06% time consumptions than traditional Gabor-based methods. Since the eight images are extremely bad, a little improvement is very meaningful.

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References

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Author information

Authors and Affiliations

  1. Key Lab on Opto-Electronic Technique of State Education Ministry, Chongqing University, 400044, Chongqing, P.R. China

    Xuchu Wang, Jianwei Li, Weimin Chen & Wei Wang

  2. College of Physics and Information Techniques, Chongqing Normal University, 400047, Chongqing, P.R. China

    Yanmin Niu

Authors
  1. Xuchu Wang
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  2. Jianwei Li
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  3. Yanmin Niu
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  4. Weimin Chen
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  5. Wei Wang
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Editor information

Editors and Affiliations

  1. Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences,  

    Stan Z. Li

  2. National Laboratory of Pattern Recognition, Institute of Automation, CAS,  

    Zhenan Sun

  3. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  4. Exploratory Computer Vision Group, IBM T.J. Watson Research Center, 10598, Yorktown Heights, NY

    Sharath Pankanti

  5. CNRS LTCI/TSI Paris, 46 rue Barrault, 75634, Paris Cedex 13, France

    Gérard Chollet

  6. Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    David Zhang

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© 2005 Springer-Verlag Berlin Heidelberg

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Wang, X., Li, J., Niu, Y., Chen, W., Wang, W. (2005). Adaptive Fingerprint Enhancement by Combination of Quality Factor and Quantitative Filters. In: Li, S.Z., Sun, Z., Tan, T., Pankanti, S., Chollet, G., Zhang, D. (eds) Advances in Biometric Person Authentication. IWBRS 2005. Lecture Notes in Computer Science, vol 3781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569947_14

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  • DOI: https://doi.org/10.1007/11569947_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29431-3

  • Online ISBN: 978-3-540-32248-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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