A classification approach to multi-biometric score fusion

Authors:
Yan Ma;Bojan Cukic;Harshinder Singh
Affiliations:
Department of Statistics, West Virginia University, Morgantown, WV;Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV;Department of Statistics, West Virginia University, Morgantown, WV
Venue:
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Year:
2005

Citing 7
Cited 7

Bagging predictors

Machine Learning
On Combining Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Random Forests

Machine Learning
Information fusion in biometrics

Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Multimodal biometrics: issues in design and testing

Proceedings of the 5th international conference on Multimodal interfaces
Application of majority voting to pattern recognition: an analysis of its behavior and performance

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An introduction to biometric recognition

IEEE Transactions on Circuits and Systems for Video Technology

Evaluation and analysis of a face and voice outdoor multi-biometric system

Pattern Recognition Letters
A New Adaptive Combination Approach to Score Level Fusion for Face and Iris Biometrics Combining Wavelets and Statistical Moments

ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Score Fusion by Maximizing the Area under the ROC Curve

IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Improving the Accuracy of a Score Fusion Approach Based on Likelihood Ratio in Multimodal Biometric Systems

ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Likelihood ratio based features for a trained biometric score fusion

Expert Systems with Applications: An International Journal
Efficient person identification by fusion of multiple palmprint representations

ICISP'10 Proceedings of the 4th international conference on Image and signal processing
A random forest system combination approach for error detection in digital dictionaries

HYBRID '12 Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data

Quantified Score

Hi-index	0.00

Visualization

Abstract

The use of biometrics for identity verification of an individual is increasing in many application areas such as border/port entry/exit, access control, civil identification and network security. Multi-biometric systems use more than one biometric of an individual. These systems are known to help in reducing false match and false non-match errors compared to a single biometric device. Several algorithms have been used in literature for combining results of more than one biometric device. In this paper we discuss a novel application of random forest algorithm in combining matching scores of several biometric devices for identity verification of an individual. Application of random forest algorithm is illustrated using matching scores data on three biometric devices: fingerprint, face and hand geometry. To investigate the performance of the random forest algorithm, we conducted experiments on different subsets of the original data set. The results of all the experiments are exceptionally encouraging.