Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Scale-Space Properties of the Multiscale Morphological Dilation-Erosion
IEEE Transactions on Pattern Analysis and Machine Intelligence
FVC2000: Fingerprint Verification Competition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Quality Measures of Fingerprint Images
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Multiscale Morphological Image Simplification
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
K-means based fingerprint segmentation with sensor interoperability
EURASIP Journal on Advances in Signal Processing
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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.