Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems (Paperback, 1st ed. 2017)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computer Science
Release date:	May 2017
First published:	2017
Authors:	Ilaiah Kavati • Munaga V. N. K. Prasad • Chakravarthy Bhagvati
Dimensions:	235 x 155 x 5mm (L x W x T)
Format:	Paperback
Pages:	67
Edition:	1st ed. 2017
ISBN-13:	978-3-319-57659-6
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
LSN:	3-319-57659-3
Barcode:	9783319576596

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