We present a residual learning-based convolutional neural network, referred to as
DeepResPore, for detection of pores in high-resolution fingerprint images. Specifically, the …

Fingerprint analysis involves the comparison of a latent print and an exemplar using the
standard ACE-V methodology. The uniqueness and persistence of fingerprints form the …

Pore detection for fingerprint recognition has gained much research attention in recent
years, in view of the existence of large number of pores in a small fingerprint segment and …

Latent fingerprint is considered as the key evidence during crime scene investigations.
Various powder and chemical methods are available for visualizing the latent fingerprints as …

The report assesses the technology readiness and availability of new functionalities–based
on automatic fingermark and palmmark recognition technologies–for their integration into …

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 …

Abstract Machine learning (ML) techniques are part of artificial intelligence. ML involves
imitating human behavior in solving different problems, such as object detection, text …

Fingerprint retrieval aims to identify a query fingerprint image in a large database using
indexing algorithms. Because of the abundant level 3 pore features within high-resolution …

The primary reason behind the increase in criminal activities in the post‐industrialization era
is the increase in human population due to relocation in urban establishments for purposes …

This paper presents an improved fingerprint recognition system for overlapping fingerprint of
two fingers. The developed system can automatically and precisely separate an overlapping …