Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems

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 mi...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Kavati, Ilaiah (Συγγραφέας), Prasad, Munaga V.N.K (Συγγραφέας), Bhagvati, Chakravarthy (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
Σειρά:SpringerBriefs in Computer Science,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Kavati, Ilaiah.  |e author. 
245 1 0 |a Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems  |h [electronic resource] /  |c by Ilaiah Kavati, Munaga V.N.K. Prasad, Chakravarthy Bhagvati. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2017. 
300 |a XVII, 67 p. 29 illus.  |b online resource. 
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505 0 |a 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. 
520 |a 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. 
650 0 |a Computer science. 
650 0 |a Special purpose computers. 
650 0 |a Information storage and retrieval. 
650 0 |a Biometrics (Biology). 
650 1 4 |a Computer Science. 
650 2 4 |a Biometrics. 
650 2 4 |a Security. 
650 2 4 |a Information Storage and Retrieval. 
650 2 4 |a Special Purpose and Application-Based Systems. 
700 1 |a Prasad, Munaga V.N.K.  |e author. 
700 1 |a Bhagvati, Chakravarthy.  |e author. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783319576596 
830 0 |a SpringerBriefs in Computer Science,  |x 2191-5768 
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950 |a Computer Science (Springer-11645)