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access icon free Combining Gabor filtering and classification dictionaries learning for fingerprint enhancement

  • Author(s): Shifei Ding 1 1 ; Weixin Bian 1, 2 1, 2 ; Hongmei Liao 1 1 ; Tongfeng Sun 1 1 ; Yu Xue 3 3
    • View affiliations
    • Affiliations: 1: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, People's Republic of China ;
      2: School of Mathematics and Computer Science, Anhui Normal University, Wuhu 241003, People's Republic of China ;
      3: School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, People's Republic of China
  • Source: Volume 6, Issue 6, November 2017, p. 438 – 447
    DOI:  10.1049/iet-bmt.2016.0161 , Print ISSN 2047-4938, Online ISSN 2047-4946
© The Institution of Engineering and Technology
Received 23/10/2016, Accepted 03/04/2017, Revised 29/03/2017, Published 06/04/2017

This study presents a new method for enhancing fingerprint image. The process of the enhancement is divided into two phases: fingerprint is first enhanced using Gabor filtering and then the enhanced fingerprint can be further enhanced by using sparse representation with the priori information of ridge pattern based on classification dictionaries learning. In the second stage, first, the orientations of fingerprint patches are estimated by the weighted linear projection analysis and the quality of patches are evaluated by the coherence of point orientations. Second, the training patches are classified into eight groups based on their own orientations, and the training samples of each class are selected from candidate patches by their own quality. The corresponding classification dictionaries are learned in frequency domain. Finally, the fingerprint image is enhanced based on spectra diffusion by using classification dictionaries learning. The experiments are carried out using various fingerprint enhancement methods. The experiments show that the proposed method achieves better results in comparison with other methods, and can significantly improve the performance of automatic fingerprint identification system.

Inspec keywords: image enhancement; image representation; frequency-domain analysis; image classification; fingerprint identification

Other keywords: weighted linear projection analysis; fingerprint patch orientations; frequency domain; automatic fingerprint identification system; training patch classification; Gabor filtering; ridge pattern; performance improvement; fingerprint image enhancement; spectra diffusion; sparse representation; classification dictionaries learning

Subjects: Image recognition; Mathematical analysis; Computer vision and image processing techniques; Mathematical analysis

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