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Overlapped Fingerprint Separation Based on Deep Learning

Published: 12 November 2018 Publication History

Abstract

Biometrics and artificial intelligence play the important roles of recent technology. In biometrics, fingerprint is one of the most widely used identification methods. However, most of this kind applications only focus on single fingerprint processing but lack discussion of recognition of overlapped fingerprint due to its complexity. In fact, overlapped fingerprints are much more common on the criminal spot and nowadays we still rely on the inefficient manual operation to separate those overlapped fingerprints. So, we purpose our automatic, accurate, and even more efficient method using convolutional neural network to deal with the overlapped fingerprints problem. In experimental result, not only the single and multi-fingerprint latent test has 92.39% and 97.1% average accurate rate respectively, but we also got 92.19% and 95.84% correct rate respectively in the overlapped and non-overlapped range detection tests. The result shows that we could actually assist the fingerprint separation work automatically and efficiently with our own method.

References

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Fan, X., Liang, D. and Zhao, L. A scheme for separating overlapped fingerprints based on partition mask, (in Chinese) Comput. Eng., vol. 40, no. 2, p. 80--81, 2004.
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Cited By

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  • (2023)Separation of Overlapped Fingerprint Images using Deep Learning2023 International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS)10.1109/ICAECIS58353.2023.10169966(233-238)Online publication date: 19-Apr-2023

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cover image ACM Other conferences
DMIP '18: Proceedings of the 2018 International Conference on Digital Medicine and Image Processing
November 2018
88 pages
ISBN:9781450365789
DOI:10.1145/3299852
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 November 2018

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Author Tags

  1. Convolutional neural network
  2. Deep learning
  3. Overlapped fingerprint range partition

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  • (2023)Separation of Overlapped Fingerprint Images using Deep Learning2023 International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS)10.1109/ICAECIS58353.2023.10169966(233-238)Online publication date: 19-Apr-2023

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