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E-grāmata: Efficient Biometric Indexing and Retrieval Techniques for Large-Scale Systems

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  • Formāts: PDF+DRM
  • Sērija : SpringerBriefs in Computer Science
  • Izdošanas datums: 09-May-2017
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319576602
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Efficient Biometric Indexing and Retrieval Techniques for Large-Scale SystemsPalielināt
  • Formāts: PDF+DRM
  • Sērija : SpringerBriefs in Computer Science
  • Izdošanas datums: 09-May-2017
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319576602
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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.

IntroductionHierarchical Decomposition of Extended Triangulation for Fingerprint IndexingAn Efficient Score-Based Indexing Technique for Fast Palmprint RetrievalA New Cluster-Based Indexing Technique for Palmprint Databases Using Scores and Decision-Level FusionConclusions and Future Scope
1 Introduction
1(20)
1.1 Introduction
1(2)
1.2 Biometric Recognition
3(3)
1.2.1 Verification
3(2)
1.2.2 Identification
5(1)
1.3 Indexing
6(2)
1.3.1 Challenges
7(1)
1.4 Biometric Indexing Techniques
8(4)
1.4.1 Key Feature Point Based Indexing Approaches
9(1)
1.4.2 Triplet-Based Indexing Approaches
10(1)
1.4.3 Match Score Based Indexing Approaches
11(1)
1.4.4 Other Indexing Approaches
12(1)
1.5 Benchmarking in Indexing and Performance Evaluation
12(4)
1.5.1 Databases
14(1)
1.5.2 Performance Metrics
14(2)
1.6 Summary
16(5)
References
16(5)
2 Hierarchical Decomposition of Extended Triangulation for Fingerprint Indexing
21(20)
2.1 Introduction
21(1)
2.2 Indexing Framework
22(8)
2.2.1 Minutiae Extraction
22(1)
2.2.2 Computation of Delaunay Triangulation
23(1)
2.2.3 Retrieval of Extended Triplet Set
24(2)
2.2.4 Hierarchical Decomposition of Extended Set
26(1)
2.2.5 Enrollment
26(4)
2.3 Query Identification
30(1)
2.4 Experimental Results
31(7)
2.4.1 Parameter Selection
32(1)
2.4.2 Results
33(2)
2.4.3 Comparison with Other Related Approaches
35(2)
2.4.4 Retrieval Time
37(1)
2.5 Summary
38(3)
References
39(2)
3 Efficient Score-Based Indexing Technique for Fast Palmprint Retrieval
41(12)
3.1 Introduction
41(1)
3.2 Indexing
42(3)
3.2.1 Feature Extraction
43(1)
3.2.2 Index Code Computation
43(1)
3.2.3 Index Table Creation and User Enrolment
44(1)
3.3 Retrieval of Best Matches for a Query
45(1)
3.4 Selection of Sample Images
46(1)
3.4.1 Max-variance Method
47(1)
3.4.2 k-Means Clustering
47(1)
3.5 Experimental Results
47(3)
3.5.1 Neighborhood Size (λ)
47(1)
3.5.2 Selection Rules for Sample Palmprints
48(1)
3.5.3 Results and Performance Comparison
48(2)
3.5.4 Retrieval Time
50(1)
3.6 Summary
50(3)
References
50(3)
4 A New Cluster-Based Indexing Technique for Palmprint Databases Using Scores and Decision-Level Fusion
53(12)
4.1 Introduction
53(1)
4.2 Selection of Sample Images
54(1)
4.3 Indexing
55(1)
4.4 Query Identification
56(3)
4.4.1 Fusion of Decisions Output
58(1)
4.5 Experimental Results
59(4)
4.5.1 Results
59(1)
4.5.2 Retrieval Time
60(1)
4.5.3 Scalability of the System
60(1)
4.5.4 Effect of Feature Type on the System Performance
60(1)
4.5.5 Comparison with Multi-biometric Systems
61(2)
4.5.6 Comparison with Other Related Indexing Techniques
63(1)
4.6 Summary
63(2)
References
64(1)
5 Conclusions and Future Scope
65
5.1 Salient Features of the Contributions
65(1)
5.2 Future Scope
66
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