<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Fusion of multiple algorithms utilizes as much information as possible from each algorithm for enhancing the performance of the biometric authentication system. It is a big challenge to formulate a single algorithm for any biometric authentication system to addresses the problem of illumination, orientations and pose variations. The palmprint features are extracted using two feature extraction algorithms namely contourlet transform with principal component analysis and dual-tree complex wavelet transform. The match scores obtained from matching modules were normalized using z-score and fused with different score level fusion schemes namely sum-rule,weighted sum-rule, and Support Vector Machine (SVM) fusion, respectively. The experimental results show that SVM score level fusion lead to an increased performance for the proposed multi-algorithmic palmprint authentication system with genuine acceptance rate of 98% for 0.1% false acceptance rate, and equal error rate of 1.5% compared to weighted sum-rule and sum-rule fusion schemes.</p>
</abstract>

Fusion of multiple algorithms utilizes as much information as possible from each algorithm for enhancing the performance of the biometric authentication system. It is a big challenge to formulate a single algorithm for any biometric authentication system to addresses the problem of illumination, orientations and pose variations. The palmprint features are extracted using two feature extraction algorithms namely contourlet transform with principal component analysis and dual-tree complex wavelet transform. The match scores obtained from matching modules were normalized using z-score and fused with different score level fusion schemes namely sum-rule,weighted sum-rule, and Support Vector Machine (SVM) fusion, respectively. The experimental results show that SVM score level fusion lead to an increased performance for the proposed multi-algorithmic palmprint authentication system with genuine acceptance rate of 98% for 0.1% false acceptance rate, and equal error rate of 1.5% compared to weighted sum-rule and sum-rule fusion schemes.

Multi-algorithmic Palmprint Authentication System Based on Score Level Fusion

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Multi-algorithmic Palmprint Authentication System Based on Score Level Fusion"}

Fusion of multiple algorithms utilizes as much information as possible from each algorithm for enhancing the performance of the biometric authentication...

Process type	Execution time (ms)
Preprocessing	25
Feature extraction	275
Pattern matching	50
Total execution time	350

Process type	Execution time (ms)
Preprocessing	25
Feature extraction	250
Pattern matching	50
Total execution time	325

Process type	Execution time (ms)
Preprocessing	25
Feature extraction	350
Pattern matching	50
Score normalization	100
Fusion at score level	250
Total execution time	775

Multi-algorithmic Palmprint Authentication System Based on Score Level Fusion

Article Category: Research-Article

Data publikacji: 05 wrz 2018

Zakres stron: 1 - 11

DOI: https://doi.org/10.21307/ijssis-2018-006

Słowa kluczowe
Contourlet transform, Dual-Tree Complex Wavelet Transform, equal error rate, false acceptance rate, genuine acceptance rate, principal component analysis, Support Vector Machine

© 2018 C. Murukesh et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Fig. 1

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Execution time calculation for contourlet transform based palmprint recognition system (1 sample of each user).

Execution time calculation for DT-CWT based palmprint recognition system (1 sample of each user).

Execution time calculation for multi-algorithmic palmprint recognition system (1 sample of each user).

Multi-algorithmic Palmprint Authentication System Based on Score Level Fusion

Article Category: Research-Article

Data publikacji: 05 wrz 2018

Zakres stron: 1 - 11

DOI: https://doi.org/10.21307/ijssis-2018-006

Słowa kluczoweContourlet transform, Dual-Tree Complex Wavelet Transform, equal error rate, false acceptance rate, genuine acceptance rate, principal component analysis, Support Vector Machine

© 2018 C. Murukesh et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Fig. 11

Fig. 12

Execution time calculation for contourlet transform based palmprint recognition system (1 sample of each user).

Execution time calculation for DT-CWT based palmprint recognition system (1 sample of each user).

Execution time calculation for multi-algorithmic palmprint recognition system (1 sample of each user).

Słowa kluczowe
Contourlet transform, Dual-Tree Complex Wavelet Transform, equal error rate, false acceptance rate, genuine acceptance rate, principal component analysis, Support Vector Machine