Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems

di Ilaiah Kavati (Autore)

Munaga V.N.K. Prasad (Autore)

Chakravarthy Bhagvati (Autore)

Springer International Publishing AG, 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.

• Autore: Ilaiah Kavati, Munaga V.N.K. Prasad, Chakravarthy Bhagvati
• Editore: Springer International Publishing AG
• Collana: SpringerBriefs in Computer Science
• Anno: 2017
• Rilegatura: Paperback / softback
• Pagine: 67 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319576596

Testo in English