A New Multibiometric Identification Method Based on a Decision Tree and a Parallel Processing Strategy

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The unimodal biometric systems cannot be always used reliably to perform the recognition of persons. Using several modalities, we can enhance the recognition rate at the cost of more processing time. In this paper, we propose a new alternative based on a multibiometric fusion approach for the identification of persons using two modalities the iris and the fingerprint. The fusion approach is performed at scores level based on a classification method by a decision tree and a combination method by the sum. In order to overcome the processing time problem, we propose a parallel processing strategy for both unimodal systems in a computer that has a multicore processor. The results obtained, after conducting several tests, confirm that the proposed methods helped significantly to optimize the performance of the whole multimodal system by offering a good compromise between the identification recognition rate and the identification response time.
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Multibiometric Fusion; Fingerprint; Iris; Multi-Core Processor; Parallel Processing

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