DOIONLINE 
DOIONLINE Publish In |
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC |
 Journal Home Volume Issue |
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Issue |
Volume-12,Issue-2 ( Feb, 2024 ) | |||||||||
Paper Title |
Multibiome –A Multimodal Biometric System With Iris and Fingerprint Recognition for Security Applications | |||||||||
Author Name |
Himagowri V, Ekta N Katti, Vijaylaxmi Dongarage, S L Nithyananda Rao, Anuros Thomas K | |||||||||
Affilition |
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Pages |
15-21 | |||||||||
Abstract |
In this paper, a multimodal biometric system with Iris and Fingerprint Recognition was introduced, employing Convolutional Neural Networks (CNN) for constructing both recognition models. The system encompasses a preprocessing phase where input iris and fingerprint images undergo enhancement. Subsequently, during the recognition phase, the preprocessed images are fed into the respective CNN models for classification. To enhance theoverall biometric recognition accuracy, an integration phase is introduced, involving decision level fusion. The integrated features from both modalities are processed through a joint decision-making system, which declares a successful match only when both the Iris and Fingerprint Recognition modules independently identify the input biometric data and their integrated decision aligns. This integration step aims to improve system reliability and security by requiring a consensus from both modalities, providing a robust solution for multimodal biometric authentication. Keywords - CNN, Canny Edge Detection, Iris Recognition, Fingerprint Recognition, Integration | |||||||||
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