Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems
Buch in deiner Nähe kaufen
Beschreibung
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.
Presents an efficient indexing approach using minutiae triplets for biometric databases Describes a score-based indexing technique that demonstrates a decreased retrieval time and enhanced identification performance compared to other match score-based approaches Introduces an efficient clustering-based indexing technique, using an adaptive clustering approach to the selection of sample images to make the system suitable for large-scale applications Includes supplementary material: sn.pub/extras Includes supplementary material: sn.pub/extras
Autor*in
Ilaiah Kavati
Themen in »Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems«
Biometrics Information retrieval Large-scale systems Search indexing Pattern recognition