@misc{10481/64942,
year = {2015},
url = {http://hdl.handle.net/10481/64942},
abstract = {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 models considered for singular point
detection and for orientation map extraction. Then, we focus on the different learning models considered to
build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction,
singular point detection, orientation extraction and learning methods are presented. A critical view of the
existing literature have led us to present a discussion on the existing methods and their drawbacks such as
difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On
this account, an experimental analysis of the most relevant methods is carried out in the second part of this
paper, and a new method based on their combination is presented.},
organization = {Research Projects CAB(CDTI) 	
TIN2011-28488
TIN2013-40765},
organization = {Spanish Government

FPU12/04902},
publisher = {ELSEVIER},
keywords = {Fingerprint classification},
keywords = {Feature extraction},
keywords = {Classification},
keywords = {Fingerprint recognition},
keywords = {SVM},
keywords = {Neural networks},
keywords = {Ensemble},
keywords = {Orientation Map},
keywords = {Singular Points},
title = {A Survey of Fingerprint Classification Part I: Taxonomies on Feature Extraction Methods and Learning Models},
doi = {10.1016/j.knosys.2015.02.008},
author = {Galar, Mikel and Peralta, Daniel and Triguero, Isaac and García López, Salvador and Benítez Sánchez, José Manuel and Herrera Triguero, Francisco},
}