Skip to main content

Strategies for intelligent interaction management and usability of biometric systems

Wu, Qianqian (2016) Strategies for intelligent interaction management and usability of biometric systems. Doctor of Philosophy (PhD) thesis, University of Kent,. (KAR id:56887)

PDF
Language: English
Download (3MB) Preview
[thumbnail of 210Thesis.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format

Abstract

Fingerprint biometric systems are one of the most popular biometric systems in current use, which takes a standard measure of a person's fingerprint to compare against the measure from an original stored template, which they have pre-acquired and associated with the known personal identification claimed by the user. Generally, the fingerprint biometric system consists of three stages including a data acquisition stage, a feature extraction stage and a matching extraction. This study will explore some essential limitations of an automatic fingerprint biometric system relating to the effects of capturing poor quality fingerprint images in a fingerprint biometric system and will investigate the interrelationship between the quality of a fingerprint image and other primary components of a fingerprint biometric system, such as the feature extraction operation and the matching process. In order to improve the overall performance of an automatic fingerprint biometric system, the study will investigate some possible ways to overcome these limitations. With the purpose of acquisition of an acceptable quality of fingerprint images, three components/enhancements are added into the traditional fingerprint recognition system in our proposed system. These are a fingerprint image enhancement algorithm, a fingerprint image quality evaluation algorithm and a feedback unit, the purpose of which is to provide analytical information collected at the image capture stage to the system user. In this thesis, all relevant information will be introduced, and we will also show some experimental results obtained with the proposed algorithms, and comparative studies with other existed algorithms will also be presented.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Fairhurst, Michael
Uncontrolled keywords: Fingerprint image enhancement Fingerprint image quality assessment Human-biometric-sensor interaction evaluation
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Users 1 not found.
Date Deposited: 19 Aug 2016 15:00 UTC
Last Modified: 16 Feb 2021 13:36 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/56887 (The current URI for this page, for reference purposes)
  • Depositors only (login required):