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
if you want this code then contact us on....
Contact
Mobile Number: +91-9637253197
Whatsup Number: +91-9637253197
Email ID: matlabprojects07@gmail.com
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