Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.692358
Title: Strategies for intelligent interaction management and usability of biometric systems
Author: Wu, Qianqian
ISNI:       0000 0004 5918 3163
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2016
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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.
Supervisor: Fairhurst, Michael Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.692358  DOI: Not available
Keywords: Q Science
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