Collaborative filtering model for enhancing fingerprint image

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.