Multimodal Classification Using Feature Level Fusion and SVM

Provided by: International Journal of Computer Applications
Topic: Security
Format: PDF
The use of biometrics in the field of enhancing security and authentication in sensitive systems is a rapidly evolving technology. The increasing attacks and decreasing security in unimodal systems have resulted in designing multimodal systems combining different biometric traits. A lot of research has already been done in designing multimodal systems with fusion at rank and match-score level using different classifiers such as Bayesian classifiers, LDA, ANNs and SVMs. In this paper, a multimodal system is designed by integrating face, fingerprint and palmprint based on feature level fusion.

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