Statistical Evaluation of Image Quality Measures for Improving Iris Recognition Performance

Authors

  • Sonali S. Gaikwad Shree Shivaji Science and Arts College, Chikli, Dist. Buldhana, Maharashtra, India
  • S. Gaikwad J Department of Computer Science and Information Technology, Dr. B. A. M. University, Aurangabad, Maharashtra,
  • R. Manza R Department of Computer Science and Information Technology, Dr. B. A. M. University, Aurangabad, Maharashtra,

DOI:

https://doi.org/10.26438/ijcse/v9i9.15

Keywords:

Quality Measure, , Iris Recognition System, Biometric, PSNR, MSE, MAXERR, L2RAT

Abstract

Iris image quality assessment is a strategy of estimating data substance of iris imagery at the phase of iris acquisition or at early preprocessing stage. The information substance might be taken to be utilized for iris identification dependent on a single image. The image might be disposed of, or joined with other imagery to improve recognition abilities of an iris system. Evaluate quality metrics would be the rules in settling on choices with respect to additional means regarding gained imagery. Implement this algorithm on open source iris databases (IIT Delhi, UBIRIS and UPOL Iris Database). We compare with the support of quality measure parameters with both original iris image and enhanced iris images. The consequential images quality is tested by using quality measures like PSNR, MSE, MAXERR, L2RAT, it is found that quality has been enhanced. Hence it is shown that the recognition rate is rises.

References

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Published

2021-09-30
CITATION
DOI: 10.26438/ijcse/v9i9.15
Published: 2021-09-30

How to Cite

[1]
S. S. Gaikwad, J. S. Gaikwad, and R. R. Manza, “Statistical Evaluation of Image Quality Measures for Improving Iris Recognition Performance”, Int. J. Comp. Sci. Eng., vol. 9, no. 9, pp. 1–5, Sep. 2021.

Issue

Vol. 9 No. 9 (2021): IJCSE September Edition

Section

Research Article

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