Abstract Sweat pore, one of the level 3 features of fingerprint, has attracted much attention in
fingerprint recognition. Traditional sweat pores on surface fingerprint are unclear or blurred …

As the Level 3 features of fingerprint, sweat pores have attracted attention in the field of
fingerprint recognition and have been successfully applied to automatic fingerprint …

Sweat pores are gaining recognition as a secure, reliable, and identifiable third-level
fingerprint feature. Challenges arise in collecting sweat pores when fingers are …

Most fingerprint recognition systems use Level 1 characteristics (ridge flow, orientation, and
frequency) and Level 2 features (minutiae points) to recognize individuals. Level 3 features …

Sweat pores have been proved to be discriminative and successfully used for automatic
fingerprint recognition. It is crucial to extract pores precisely to achieve high recognition …

Optical coherence tomography (OCT), as a non-destructive and high-resolution fingerprint
acquisition technology, is robust against poor skin conditions and resistant to spoof attacks …

The public demand for personal safety is increasing rapidly. Fingerprint features as the most
commonly used bio-signature need to improve their safety continuously. The third level …

In this study, an automatic algorithm has been presented based on a convolutional neural
network (CNN) employing U-net. An ellipsoid and an ellipse were applied for approximation …

Sweat pores on the human fingertip have meaningful patterns that enable individual
identification. Although conventional automatic fingerprint identification systems (AFIS) have …

Biometric access control systems often employ fingerprint recognition based on the analysis
of ridge patterns and minutiae. The inclusion of finer details, such as sweat pores, increases …