TY  - BOOK
AU  - Kavati,Ilaiah
AU  - Prasad,Munaga V.N.K.
AU  - Bhagvati,Chakravarthy
ED  - SpringerLink (Online service)
TI  - Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems
T2  - SpringerBriefs in Computer Science,
SN  - 9783319576602
AV  - QH323.5 
U1  - 570.15195 23
PY  - 2017///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Biometrics (Biology)
KW  - Data protection
KW  - Information storage and retrieval
KW  - Special purpose computers
KW  - Biometrics
KW  - Security
KW  - Information Storage and Retrieval
KW  - Special Purpose and Application-Based Systems
N1  - Introduction -- Hierarchical Decomposition of Extended Triangulation for Fingerprint Indexing -- An Efficient Score-Based Indexing Technique for Fast Palmprint Retrieval -- A New Cluster-Based Indexing Technique for Palmprint Databases Using Scores and Decision-Level Fusion -- Conclusions and Future Scope; Available to subscribing member institutions only. Доступно лише організаціям членам підписки
N2  - 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
UR  - https://doi.org/10.1007/978-3-319-57660-2
ER  -