Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems / SpringerBriefs in Computer Science (PDF)
(Sprache: Englisch)
This work presents a review of different indexing techniques designed to enhance the speed and efficiency of searches over large biometric databases. The coverage includes an extended Delaunay triangulation-based approach for fingerprint biometrics,...
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This work presents a review of different indexing techniques designed to enhance the speed and efficiency of searches over large biometric databases. The coverage includes an extended Delaunay triangulation-based approach for fingerprint biometrics, involving a classification based on the type of minutiae at the vertices of each triangle. This classification is demonstrated to provide improved partitioning of the database, leading to a significant decrease in the number of potential matches during identification. This discussion is then followed by a description of a second indexing technique, which sorts biometric images based on match scores calculated against a set of pre-selected sample images, resulting in a rapid search regardless of the size of the database. The text also examines a novel clustering-based approach to indexing with decision-level fusion, using an adaptive clustering algorithm to compute a set of clusters represented by a 'leader' image, and then determining the index code from the set of leaders. This is shown to improve identification performance while using minimal resources.
Bibliographische Angaben
- Autoren: Ilaiah Kavati , Munaga V. N. K. Prasad , Chakravarthy Bhagvati
- 2017, 1st ed. 2017, 67 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319576607
- ISBN-13: 9783319576602
- Erscheinungsdatum: 09.05.2017
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- Grösse: 3.06 MB
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Englisch
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