Intelligent Multimodal Identification System based on Local Feature Fusion between Iris and Finger Vein

rowedah hussien


The identification process is one of the important processes to achieve safety, which is used daily in many areas such as the attendance system, various Internet or social sites, personal accounts inside banks and other important areas. In this article, a smart multimodal pattern verification model for identifying a person's identity is recommended based on the Scale Invariant Feature Transform (SIFT) method. This system is identified the iris and finger vein unique patterns and features for each individual to overcome many challenges such as identity fraud, poor image quality, noise and instability of the surrounding environment. This system provides an effective fusion scheme based on the incorporation of different features of each biometric system and thus increase the efficiency that cannot be achieved in a single-modal identification system. Several experiments were performed on a dataset containing 50 people and using the Hamming distance algorithm to measure the similarity between a person and previously entered data. The results of the proposed system were provided a higher accuracy of 98%, with FAR and FRR of 0.0015% and 0.025%, respectively.

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