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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems

Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems

Kavati, Ilaiah
Prasad, Munaga V. N. K.
Bhagvati, Chakravarthy

Paperback

Series: Springerbriefs in Computer Science

General ComputersComputer SecuritySystem Administration

ISBN10: 3319576593
ISBN13: 9783319576596
Publisher: Springer Nature
Published: May 16 2017
Pages: 67
Weight: 0.30
Height: 0.18 Width: 6.14 Depth: 9.21
Language: English
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.

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