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Home > Archive>Volume 30, Issue 6, 2019 >1886-1900. DOI:10.13328/j.cnki.jos.005421
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Combined Filtering and DBM Reconstructing for Fingerprint Enhancement
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National Natural Science Foundation of China (61672522, 61379101); Anhui Provincial Natural Science Foundation (No.1708085MF145)

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    Abstract:

    The enhancement of fingerprint plays an important role in automatic fingerprint identification system. In order to make up for the shortcomings of the traditional fingerprint enhancement, this study proposes a novel algorithm by using orientation Gaussian bandpass filter (OGBPF) to enhance the fingerprint firstly, and then the deep Boltzmann machine (DBM) with orientation selection is employed to reconstruct these regions that are enhanced incorrectly in the first phase. The fingerprint is enhanced based on the quality grading scheme and the composite window strategy. In the proposed method, the traditional enhancement method and deep learning method complement one another perfectly. To validate the performance, the proposed method has been applied to fingerprint enhancement on the FVC2004 databases. Experiments show that, compared with the state-of-the-art enhancement methods, the proposed method is more accurate and more robust against noise, and can achieve better results.

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卞维新,丁世飞,张楠,张健,赵星宇.结合滤波和深度玻尔兹曼机重构的指纹增强.软件学报,2019,30(6):1886-1900

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History
  • Received:June 01,2017
  • Revised:July 16,2017
  • Online: June 04,2019
Links:Institute of Software, CASChina Computer FederationCASNSFC
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