|
PPN: |
1751272680 
|
|
Titel: |
Biometric Recognition : 13th Chinese Conference, CCBR 2018, Urumqi, China, August 11-12, 2018, Proceedings
|
|
Personen: |
|
|
Ort/Jahr: |
Cham : Springer International Publishing AG, 2018 |
|
Sprache/n: |
Englisch |
|
Copyright-Datum: |
©2018 |
|
Umfang: |
1 online resource (755 pages) |
|
Schriftenreihe: |
|
|
Anmerkung: |
Description based on publisher supplied metadata and other sources. |
|
Bibliogr. Zusammenhang: |
|
|
ISBN: |
978-3-319-97909-0
Weitere Ausgaben: 978-3-319-97908-3 (Printausgabe)
|
|
Schlagwörter: |
|
|
Klassifikation: |
Dewey Decimal Classification: 6
|
 |
Inhalt:
|
Intro -- Preface -- Organization -- Contents -- Hand-Based Biometrics -- Dorsal Hand Vein Recognition Method Based on Multi-bit Planes Optimization -- Abstract -- 1 Introduction -- 2 The Generation of Multi-bit Planes -- 2.1 Collection of Images -- 2.2 Preprocessing of Image -- 3 Optimization of Multi-bit Planes -- 4 Classification Experiment Based on SqueezeNet Network -- 5 Conclusion -- Acknowledgment -- References -- A Novel Finger-Knuckle-Print Recognition Based on Batch-Normalized CNN -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Batch-Normalized CNN -- 3.1 Batch-Normalized Convolutional Neural Networks -- 3.2 ReLU Activation Function -- 4 FKP Recognition Process -- 4.1 ROI Extraction -- 4.2 Data Augmentation via Random Histogram Equalization -- 5 Experimental Results -- 5.1 PolyU Database -- 5.2 Configuration of Training Parameters -- 5.3 FKP Experimental Results -- 6 Conclusion -- Acknowledgments -- References -- A New Hand Shape Recognition Algorithm Based on Delaunay Triangulation -- Abstract -- 1 Introduction -- 2 Finger Contour Extraction -- 3 Finger Central Axis and Features Extraction -- 4 Results and Analysis -- 5 Conclusion -- Acknowledgments -- References -- Finger Vein Recognition Based on Weighted Graph Structural Feature Encoding -- Abstract -- 1 Introduction -- 2 Feature Encoding Algorithm -- 2.1 Finger-Vein Enhancement -- 2.2 SCW-LGS -- 2.3 Multi-orientation SCW-LGS -- 3 Feature Matching -- 4 Experiments and Analysis -- 4.1 Parameter Selection -- 4.2 Comparisons -- 5 Conclusions -- Acknowledgements -- References -- Fingerprint Pore Extraction Using Convolutional Neural Networks and Logical Operation -- Abstract -- 1 Introduction -- 2 Methodology Statement -- 2.1 Coarse Detection of Pore Candidates -- 2.2 CNN Architecture and Implement Details -- 2.3 Refinement -- 3 Experimental Results and Analysis. |
|
Links zum Titel:
|
|
|
Produktsigel: |
ZDB-30-PQE |
