Unsupervised Fingerprint Segmentation Based on Multiscale Directional Information

摘要

The segmentation task is an important step in automatic fingerprint classification and recognition. In this context, the term refers to splitting the image into two regions, namely, foreground and background. In this paper, we introduce a novel segmentation approach designed to deal with fingerprint images originated from different sensors. The method considers a multiscale directional operator and a scale-space toggle mapping used to estimate the image background information. We evaluate our approach on images of different databases, and show its improvements when compared against other well-known state-of-the-art segmentation methods discussed in literature.