A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models
This paper reviews the fingerprint classification literature looking at the problem from a
double perspective. We first deal with feature extraction methods, including the different …
double perspective. We first deal with feature extraction methods, including the different …
Fusion of band limited phase only correlation and width centroid contour distance for finger based biometrics
In this paper, a new approach of multimodal finger biometrics based on the fusion of finger
vein and finger geometry recognition is presented. In the proposed method, Band Limited …
vein and finger geometry recognition is presented. In the proposed method, Band Limited …
Fingerprint enhancement based on tensor of wavelet subbands for classification
Fingerprint image enhancement is a key aspect of an automated fingerprint identification
system. This paper describes an effective algorithm based on a novel lighting compensation …
system. This paper describes an effective algorithm based on a novel lighting compensation …
On the use of convolutional neural networks for robust classification of multiple fingerprint captures
Fingerprint classification is one of the most common approaches to accelerate the
identification in large databases of fingerprints. Fingerprints are grouped into disjoint …
identification in large databases of fingerprints. Fingerprints are grouped into disjoint …
On the usefulness of one-class classifier ensembles for decomposition of multi-class problems
Multi-class classification can be addressed in a plethora of ways. One of the most promising
research directions is applying the divide and conquer rule, by decomposing the given …
research directions is applying the divide and conquer rule, by decomposing the given …
An empirical study of dermatoglyphics fingerprint pattern classification for human behavior analysis
MA Bhimrao, B Gupta - Social Network Analysis and Mining, 2023 - Springer
Human measures many things consciously or subconsciously by touching and sensing
without any measurable challenges. However, measuring intangible features like human …
without any measurable challenges. However, measuring intangible features like human …
Fast fingerprint classification with deep neural networks
D Michelsanti, AD Ene, Y Guichi, R Stef… - … on Computer Vision …, 2017 - scitepress.org
Reducing the number of comparisons in automated fingerprint identification systems is
essential when dealing with a large database. Fingerprint classification allows to achieve …
essential when dealing with a large database. Fingerprint classification allows to achieve …
Fingerprint classification through standard and weighted extreme learning machines
D Zabala-Blanco, M Mora, RJ Barrientos… - applied sciences, 2020 - mdpi.com
Fingerprint classification is a stage of biometric identification systems that aims to group
fingerprints and reduce search times and computational complexity in the databases of …
fingerprints and reduce search times and computational complexity in the databases of …
A novel fingerprint classification method based on deep learning
R Wang, C Han, T Guo - 2016 23rd International Conference …, 2016 - ieeexplore.ieee.org
Fingerprint classification is an effective technique for reducing the candidate numbers of
fingerprints in the stage of matching in automatic fingerprint identification system (AFIS). In …
fingerprints in the stage of matching in automatic fingerprint identification system (AFIS). In …
Lightweight convolutional neural network based on singularity ROI for fingerprint classification
W Jian, Y Zhou, H Liu - IEEE Access, 2020 - ieeexplore.ieee.org
Fingerprint classification is a significant guarantee for efficient and accurate fingerprint
recognition, especially when dealing with one-to-many fingerprint recognition. However, due …
recognition, especially when dealing with one-to-many fingerprint recognition. However, due …