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access icon free Collaborative filtering model for enhancing fingerprint image

  • Author(s): Weixin Bian 1, 2 ; Shifei Ding 1 ; Weikuan Jia 3
    • View affiliations
  • Source: Volume 12, Issue 1, January 2018, p. 149 – 157
    DOI:  10.1049/iet-ipr.2017.0059 , Print ISSN 1751-9659, Online ISSN 1751-9667
© The Institution of Engineering and Technology
Received 16/01/2017, Accepted 01/10/2017, Revised 10/05/2017, Published 17/10/2017

Fingerprint enhancement plays a very important role in automatic fingerprint identification system. In order to ensure reliable fingerprint identification and improve fingerprint ridge structure, a novel method based on the collaborative filtering model for fingerprint enhancement is proposed. The proposed method consists of two stages. First, the original fingerprint is pre-enhanced by using Gabor filter and linear contrast stretching. Next, the pre-enhanced fingerprint is partitioned into patches in spatial domain, and then the patches are enhanced based on spectra diffusion by using the two-dimensional (2D) angular-pass filter and the 2D Butterworth band-pass filter. The proposed method takes full advantage of the ridge information and spectra diffusion with higher quality to recover the lost ridge information. To evaluate proposed method, the databases FVC2004 are employed, and the comparison experiments are carried out using various methods. Comparative experimental results show that the proposed algorithm outperforms the existing state-of-the-art methods on fingerprint enhancement.

Inspec keywords: image enhancement; collaborative filtering; Butterworth filters; band-pass filters; image filtering; fingerprint identification; Gabor filters

Other keywords: collaborative filtering model; Gabor filter; spectra diffusion; fingerprint ridge structure improvement; spatial domain; preenhanced fingerprint partitioning; automatic fingerprint identification system; linear contrast stretching; patch enhancement; 2D Butterworth band-pass filter; two-dimensional angular-pass filter; fingerprint image enhancement

Subjects: Information retrieval techniques; Image recognition; Filtering methods in signal processing; Computer vision and image processing techniques

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