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MultiBiometric Fusion: Left and Right Irises based Authentication Technique
Author(s) -
Leila Zoubida,
Réda Adjoudj
Publication year - 2017
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2017.04.02
Subject(s) - biometrics , computer science , artificial intelligence , modality (human–computer interaction) , pattern recognition (psychology) , support vector machine , segmentation , iris recognition , authentication (law) , iris (biosensor) , feature extraction , field (mathematics) , feature (linguistics) , computer vision , mathematics , linguistics , philosophy , computer security , pure mathematics
Biometric science is one of the important applications in the pattern recognition field. There are several modalities used in the biometric applications, among these different traits we choose the iris modality. Therefore, this paper proposes a multi-biometric technique which combines the both units of the iris modality: the left and the right irises. The fusion combines the advantages of the two instances. For the both units of the iris, the segmentation is realized by a modified method and the feature extraction is done by a global approach (the Daubechies wavelets). The Support Vector Machine SVM is used to obtain scores for fusion. Then the scores obtained are normalized by Min-Max method and the fusion is performed at score level by the combination of two methods: a combination method with a classification method. The Fusion is tested using four databases which are: CASIAV4 database, SDUMLAHMT database, MMU1, and MMU2 databases. The obtained results have confirmed that the multi-biometric systems are better than the mono-modal systems according to their performance.

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