
	Information Technology Journal
	Year: 2010 \| Volume: 9 \| Issue: 1 \| Page No.: 188-191 DOI: 10.3923/itj.2010.188.191

A Study of Neural Network and its Properties of Training and Adaptability in Enhancing Accuracy in a Multimodal Biometrics Scenario

Fawaz Alsaade

Abstract: The main aim of this study was to present investigations for enhancing the accuracy of multimodal biometrics by introducing the neural network into the score-level fusion process. Presently, various fusion techniques are being widely used in combining separate information from different modalities to provide complementary data. The resilient backpropagation training algorithm was used for this purpose. The effectiveness of the proposed method is to benefit from the properties of training and adaptability of the neural network technique. The experimental investigations involved the recognition mode of verification in mixed-quality data conditions. It was found during the study that by deploying such technique at the score level, the system error rate can be reduced considerably. The study presented the motivation and the potential advantages of the proposed approach and the details of the experimental study.

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How to cite this article:

Fawaz Alsaade , 2010. A Study of Neural Network and its Properties of Training and Adaptability in Enhancing Accuracy in a Multimodal Biometrics Scenario. Information Technology Journal, 9: 188-191.

DOI: 10.3923/itj.2010.188.191

URL: https://scialert.net/abstract/?doi=itj.2010.188.191

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