Abstract

Multimodal biometric system is a system that is viable in authentication and capable of carrying the robustness of the system. Most existing biometric systems ear fingerprint and face ear suffer varying challenges such as large variability, high dimensionality, small sample size and average recognition time. These lead to the degrading performance and accuracy of the system. Sequel to this, multimodal biometric system was developed to overcome those challenges. The system was implemented in MATLAB environment. Am improved self organizing feature map was used to classify the fused features into known and unknown. The performance of the developed multimodal was evaluated based on sensitivity, recognition accuracy and time. Olabode, A. O | Amusan, D. G | Ajao, T. A "An Improved Self Organizing Feature Map Classifier for Multimodal Biometric Recognition System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26458.pdfPaper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/26458/an-improved-self-organizing-feature-map-classifier-for-multimodal-biometric-recognition-system/olabode-a-o

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