Main Article Content
Currently, there are many solutions related to biometric systems for users authentication purposes
based on iris image, because, the human iris characteristics remain unalterable for each individual.
In order to improve the iris biometric system accuracy, the images captured need to reach a minimum
quality level. However, different distortion can occur in the image acquisition step, such as blurring,
affecting the global performance of the system. In this context, this research proposes a methodology
to treat the blurred images and to improve their quality. The deblurring process is a complicated task,
and most of the methodologies need the Point Spread Function (PSF) to correct the impaired image.
A method named blind deconvolution is used in this work to get the PSF value, and then it is used in
the deblurring process to improve the image quality. Experimental results demonstrated that corrected
images reached minor Hamming Distance values, considering iris images of the same user, improving
the biometric system performance. Thus, with the solution proposed, the False no-Match rate parameter
of the global system decreased from 27.82% to 4.41%.
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