Improved method for extraction of fingerprint features

Abstract

Extracting features from fingerprints is a crucial step in fingerprint verification and recognition. Here, features are represented as minutiae, such as end points and bifurcation points. Many algorithms for this issue have been developed recently. This paper presents a fingerprint feature extraction method through which minutiae are extracted directly from original gray-level fingerprint images without binarization and thinning. Our algorithm improves the performance of the existing ones along this stream. Our experimental results demonstrate that our approach can achieve better performance in both efficiency and robustness.