Overview
- 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
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (5 chapters)
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Bibliographic Information
Book Title: Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems
Authors: Ilaiah Kavati, Munaga V.N.K. Prasad, Chakravarthy Bhagvati
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-319-57660-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2017
Softcover ISBN: 978-3-319-57659-6Published: 16 May 2017
eBook ISBN: 978-3-319-57660-2Published: 09 May 2017
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XVII, 67
Number of Illustrations: 29 b/w illustrations
Topics: Biometrics, Security, Information Storage and Retrieval, Special Purpose and Application-Based Systems