Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/7949
Title: On Engineering Challenges of Applying Relevance Feedback to Fingerprint Identification Systems
Contributor(s): Welch, Mitchell  (author)orcid ; Kwan, Paul H  (author); Sajeev, Abudulkadir  (author)
Publication Date: 2010
DOI: 10.1109/CISE.2010.5676959
Handle Link: https://hdl.handle.net/1959.11/7949
Abstract: Effective fingerprint identification is critical in crime detection and many security related operations. This article investigates the use of Relevance Feedback with automatic fingerprint identification systems. It also summarises how several unique engineering challenges faced when applying relevance feedback are being addressed. Relevance feedback is a process for acquiring and using knowledge from a human user to improve the quality of results from an information retrieval system. It has been applied extensively to both text-based and images-based information retrieval systems, but not to fingerprint identification systems. Compared to automatic processes, relevance feedback has the potential to assist in faster convergence towards correct fingerprint identification and removes the reliance on black box fingerprint matching algorithm for the system's performance. Experimental results collected from a prototype software implementation confirm that relevance feedback can improve the quality of fingerprint identification queries significantly.
Publication Type: Conference Publication
Conference Name: International Conference on Computational Intelligence and Software Engineering (CiSE 2010), Wuhan, China, 10th - 12th December, 2010
Conference Details: International Conference on Computational Intelligence and Software Engineering (CiSE 2010), Wuhan, China, 10th - 12th December, 2010
Source of Publication: Proceedings of the 2010 International Conference on Computational Intelligence and Software Engineering (CiSE), p. 1-5
Publisher: IEEE: Institute of Electrical and Electronics Engineers Systems
Place of Publication: Wuhan, China
Field of Research (FOR): 080106 Image Processing
080109 Pattern Recognition and Data Mining
Socio-Economic Outcome Codes: 890299 Computer Software and Services not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Other Links: http://www.ciseng.org/2010/
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Appears in Collections:Conference Publication

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