Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493220
Title: Fingerprint classification with combined neural networks
Author: Zhang, Fan
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2009
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Abstract:
Biometric identification has been widely used in identifying a genuine person from an impostor. Fingerprint identification is becoming a very popular biometric identification technique because it has special properties: fingerprints are unique and unchangeable. With increased processing capability of computers and larger the size of fingerprint databases are increased, the demand for higher speed processing and greater processing capacity for automatic fingerprint identification systems (AFIS) has increased. APIS consists of fingerprint feature acquisition, fingerprint classification and fingerprint matching. Fingerprint classification plays a key role in fingerprint identification as efficient and accurate algorithms cannot only reduce the search time for searching large fingerprint databases, but they can also reduce the number of fingerprints that need to be searched.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.493220  DOI: Not available
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