Editing Fingerprint (section)

=== Live scan devices ===
[[File:Fingerprint scanner identification.jpg|thumb|Fingerprint being scanned]]
[[File:3DFingerprint.jpg|thumb|3D fingerprint<ref name=3DPrintsweb>{{cite magazine
 | url = http://www.technologyreview.com/computing/23549/?a=f
 | title = Touchless 3-D Fingerprinting: A new system offers better speed and accuracy
 | magazine = Technology Review
 | first = Rachel
 | last = Kremen
 | date = September 2009
 | access-date = March 17, 2010
 | archive-date = October 20, 2009
 | archive-url = https://web.archive.org/web/20091020062002/http://www.technologyreview.com/computing/23549/?a=f
 | url-status = live
 }}</ref>]]

Fingerprint image acquisition is the most critical step in an automated fingerprint authentication system, as it determines the final fingerprint image quality, which has a drastic effect on the overall system performance. There are different types of fingerprint readers on the market, but the basic idea behind each is to measure the physical difference between ridges and valleys.

All the proposed methods can be grouped into two major families: solid-state fingerprint readers and optical fingerprint readers. The procedure for capturing a fingerprint using a sensor consists of rolling or touching with the finger onto a sensing area, which according to the physical principle in use (optical, ultrasonic, capacitive, or thermal{{spaced endash}}see {{section link||Fingerprint sensors}}) captures the difference between valleys and ridges. When a finger touches or rolls onto a surface, the elastic skin deforms. The quantity and direction of the pressure applied by the user, the skin conditions and the projection of an irregular 3D object (the finger) onto a 2D flat plane introduce distortions, noise, and inconsistencies in the captured fingerprint image. These problems result in inconsistent and non-uniform irregularities in the image.<ref name=2DPrintDeform>{{cite book | title = Estimating fingerprint deformation| author = Ross A. Jain| publisher = Proceedings of the International Conference on Biometric Authentication (ICBA)| year = 2004 }}</ref> During each acquisition, therefore, the results of the imaging are different and uncontrollable. The representation of the same fingerprint changes every time the finger is placed on the sensor plate, increasing the complexity of any attempt to match fingerprints, impairing the system performance and consequently, limiting the widespread use of this [[biometric]] technology.

In order to overcome these problems, as of 2010, non-contact or touchless 3D fingerprint scanners have been developed. Acquiring detailed 3D information, 3D fingerprint scanners take a digital approach to the analog process of pressing or rolling the finger. By modelling the distance between neighboring points, the fingerprint can be imaged at a resolution high enough to record all the necessary detail.<ref name=3DPrints>{{cite book |first = Yongchang |last = Wang |author2 = Q. Hao |author3 = A. Fatehpuria  |author4 = D. L. Lau |author5 = L. G. Hassebrook|title = 2009 First IEEE International Conference on Biometrics, Identity and Security (BIdS) |year  = 2009 |chapter = Data Acquisition and Quality Analysis of 3-Dimensional Fingerprints |pages = 1–9 |publisher = IEEE conference on Biometrics, Identity and Security |location = Florida|doi = 10.1109/BIDS.2009.5507527 |isbn = 978-1424452767 |s2cid = 519064 }}</ref>