Multimodal Biometric Face and Fingerprint Recognition Using Adaptive principal Component Analysis and Multilayer Perception
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 6
Abstract
A multimodal biometric face and fingerprint recognition using neural network system based on adaptive principal component analysis and multilayer perception.To improve accuracy and performance, Reliable method for security and integrity of the biometrics data. An efficient Face and fingerprint recognition algorithm combining ridge based and Eigen face approach for parallel execution .The aim is to reduce one or more of the following -False accept rate (FAR) False reject rate (FRR) Failure to enroll rate (FTE) . Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. Experimental studies show that Unimodal biometric systems had many disadvantages regarding performance and accuracy. Multimodal biometric systems perform better than unimodal biometric systems and are popular even more complex also. We examine the accuracy and performance of multimodal biometric authentication systems using state of the art Commercial Off- TheShelf (COTS) products.
Authors and Affiliations
Praveen Kumar Nayak, Devesh Narayan
Keywords
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