| Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems 2017 Edition Contributor(s): Kavati, Ilaiah (Author), Prasad, Munaga V. N. K. (Author), Bhagvati, Chakravarthy (Author) |
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ISBN: 3319576593 ISBN-13: 9783319576596 Publisher: Springer OUR PRICE: $52.24 Product Type: Paperback Published: May 2017 |
| Additional Information |
| BISAC Categories: - Computers | Computer Vision & Pattern Recognition - Computers | Security - General - Computers | System Administration - Storage & Retrieval |
| Dewey: 004.6 |
| Series: Springerbriefs in Computer Science |
| Physical Information: 0.18" H x 6.14" W x 9.21" (0.30 lbs) 67 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |
