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Empirical Analysis on the Effect of Image Compression and Denoising Using Different Wavelets on Iris Recognition

  • Pranita BaroEmail author
  • Malaya Dutta BorahEmail author
  • Sushanta Mukhopadhyay
Conference paper
  • 80 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1192)

Abstract

The Iris recognition is commonly used as a security system due to its robustness against imposters. Iris datasets are huge and hence those datasets occupy more space. Iris image compression has become an important part of better performance like speed and data storage. The portable Iris system is in huge demand. That portable systems need to transmit the iris images through a very small bandwidth channel. To reduce the time for transferring a huge number of data over small bandwidth channel, iris file can be compressed to some extent to minimize the size. Another problem is that when an image is captured, it captures some noise that disturbs the recognition performance, so, denoising is required for noise-free images. This paper separately analyzes the impact of wavelet compression along with denoising on iris images. The compression analysis is done using Embedded Zero Tree Wavelet, the other technique used is Set Partitioning in Hierarchical Tree and the third technique used is Spatial-Orientation Tree Wavelet. Denoising is done using different wavelets Daubechies, Haar, Biorthogonal and Fejer-Korovkin. The impact of the wavelet compression and denoising techniques on recognition performance are compared with False Rejection Rate and False Acceptance Rate. The quality of a compressed image is calculated with different quality metrics. This work establishes that compression and denoising of the images minimally affect the recognition performance.

Keywords

Iris recognition Quality metric Image compression Image denoising 

Notes

Acknowledgement

The authors would like to acknowledge the Department of Computer Science and Engineering and TEQIP-III cell, National Institute of Technology Silchar for financial and infrastructural support to complete this research work.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.National Institute of Technology SilcharSilcharIndia
  2. 2.Indian Institute of Technology (ISM) DhanbadDhanbadIndia

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