Impact of Age Groups on Fingerprint Recognition

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Author

Shimon Modi and Stephen J. Elliott and Hakil Kim and Jeff Whetstone

Entry type

conference

Abstract

Ever since introduction of automated fingerprint recognition in law enforcement in the 1970s it has been utilized in applications ranging from personal authentication to civilian border control. The increasing use of automated fingerprint recognition puts on it a challenge of processing a diverse range of fingerprints. The quality control module is important to this process because it supports consistent fingerprint detail extraction which helps in identification / verification. Inherent feature issues, such as poor ridge flow, and interaction issues, such as inconsistent finger placement, have an impact on captured fingerprint quality, which eventually affects overall system performance. Aging results in loss of collagen; compared to younger skin, aging skin is loose and dry. Decreased skin firmness directly affects the quality of fingerprints acquired by sensors. Medical conditions such as arthritis may affect the user

Date

2007 – 06

Booktitle

AutoID 2007

Key alpha

agefingerprintrecognition

Publication Date

2007-06-01

Keywords

fingerprint recognition, age, elderly, young, fingerprint image quality

Language

English

BibTex-formatted data

To refer to this entry, you may select and copy the text below and paste it into your BibTex document. Note that the text may not contain all macros that BibTex supports.

@Conference{ agefingerprintrecognition,
	title = "Impact of Age Groups on Fingerprint Recognition",
	author = "Shimon Modi and Stephen J. Elliott and Hakil Kim and Jeff Whetstone",
	year = "2007",
	month = "06",
	booktitle = "AutoID 2007",
	abstract = "Ever since introduction of automated fingerprint recognition in law enforcement in the 1970s it has been utilized in applications ranging from personal authentication to civilian border control. The increasing use of automated fingerprint recognition puts on it a challenge of processing a diverse range of fingerprints. The quality control module is important to this process because it supports consistent fingerprint detail extraction which helps in identification / verification. Inherent feature issues, such as poor ridge flow, and interaction issues, such as inconsistent finger placement, have an impact on captured fingerprint quality, which eventually affects overall system performance. Aging results in loss of collagen; compared to younger skin, aging skin is loose and dry. Decreased skin firmness directly affects the quality of fingerprints acquired by sensors. Medical conditions such as arthritis may affect the user",
	keywords = "fingerprint recognition, age, elderly, young, fingerprint image quality",
	language = "English",
}