Friday, 17 July 2020

MATLAB code of fake biometric detection application to iris recognition


Hello, friends today posting one project in the field of biometric. In the last post, we have seen a fake biometric detection application to face recognition. But this post is about fake biometric detection application to iris recognition. The problem of fake biometric detection can be seen as a two-class, classification problem where an input biometric sample has to be assigned to one of two classes: real or fake. In the present work, we propose a novel parameterization using 25 general image quality measures. As the method operates on the whole image without searching for any trait-specific properties, it does not require any pre-processing steps (fingerprint segmentation, iris detection or face extraction). This characteristic minimizes its computational load. Once the feature vector has been generated the sample is classified as real (generated by a genuine trait) or fake (synthetically produced), using some simple classifiers. The parameterization proposed in the present work comprises 25 image quality measures both reference and blind. The following YouTube video shows the working of the project.

YouTube Video of the Project:  


The following figure shows the general diagram of biometric protection a method based on Image Quality Assessment (IQA) proposed in the present work. IQM stands for Image Quality Measure, FR for Full-Reference, and NR for No-Reference.

Fig: Full Reference and No reference IQA

MATLAB Implementation of the project:

Fig: True Bormetric MATLAB GUI

Fig: Fake Bormetric MATLAB GUI

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