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Latent Fingerprint Enhancement Based on Orientation Guided Sparse Representation

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Biometric Recognition (CCBR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9967))

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Abstract

Latent fingerprints are the finger skin impressions left at the crime scene by accident. They are usually of poor quality with unclear ridge structure and various overlapping patterns. This paper proposes a latent fingerprint enhancement algorithm which combines the TV image decomposition model and image reconstruction by orientation guided sparse representation. Firstly, the TV model is applied to decompose a latent fingerprint image into the texture and cartoon components. Secondly, we calculate the orientation field and the reliability of the texture image. Finally, for the low reliability region, sparse representation based on the redundant dictionary, which is constructed with Gabor functions and the specific local ridge orientation, is iteratively used to reconstruct the image. Experimental results based on NIST SD27 latent fingerprint database indicate that the proposed algorithm can not only remove various noises, but also restore the corrupted ridge structure well.

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Acknowledgement

This work was supported by National Natural Science Foundation of China under the grants No. 61375112 and 61005024.

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Authors and Affiliations

  1. Department of Instrument Science and Engineering, SEIEE, Shanghai Jiao Tong University, Shanghai, China

    Kaifeng Wei & Manhua Liu

Authors
  1. Kaifeng Wei
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  2. Manhua Liu
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Corresponding author

Correspondence to Manhua Liu .

Editor information

Editors and Affiliations

  1. Sichuan University , Chengdu, China

    Zhisheng You

  2. Tsinghua University , Beijing, China

    Jie Zhou

  3. Beihang University , Beijing, China

    Yunhong Wang

  4. Chinese Academy of Sciences , Beijing, China

    Zhenan Sun

  5. Chinese Academy of Sciences , Beijing, China

    Shiguang Shan

  6. Sun Yat-sen University , Guangzhou, China

    Weishi Zheng

  7. Tsinghua University , Beijing, China

    Jianjiang Feng

  8. Sichuan University , Chengdu, China

    Qijun Zhao

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© 2016 Springer International Publishing AG

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Wei, K., Liu, M. (2016). Latent Fingerprint Enhancement Based on Orientation Guided Sparse Representation. In: You, Z., et al. Biometric Recognition. CCBR 2016. Lecture Notes in Computer Science(), vol 9967. Springer, Cham. https://doi.org/10.1007/978-3-319-46654-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-46654-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46653-8

  • Online ISBN: 978-3-319-46654-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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