Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Level Set Evolution without Re-Initialization: A New Variational Formulation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Robust Multi-modal and Multi-unit Feature Level Fusion of Face and Iris Biometrics
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
PSO versus AdaBoost for feature selection in multimodal biometrics
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Feature selection for support vector machine-based face-iris multimodal biometric system
Expert Systems with Applications: An International Journal
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Multibiometric systems alleviate some of the drawbacks possessed by the single modal biometric trait and provide better recognition accuracy. This paper presents a multimodal system that integrates the iris, face, and gait features based on the fusion at feature level. The novelty of this research effort is that a feature subset selection scheme based on Particle Swarm Optimization (PSO) is proposed to select the optimal subset of features from the fused feature vector. In addition, we apply a Variational Level Set (VLS)-based curve evolution scheme to detect the silhouette shape structure. Experimental results indicate that the proposed approach increases biometric recognition accuracies compared to that produced by single modal biometrics.