Department of Computer Science and Technology

Technical reports

Effect of severe image compression on iris recognition performance

John Daugman, Cathryn Downing

May 2007, 20 pages

DOI: 10.48456/tr-685


We investigate three schemes for severe compression of iris images, in order to assess what their impact would be on recognition performance of the algorithms deployed today for identifying persons by this biometric feature. Currently, standard iris images are 600 times larger than the IrisCode templates computed from them for database storage and search; but it is administratively desired that iris data should be stored, transmitted, and embedded in media in the form of images rather than as templates computed with proprietary algorithms. To reconcile that goal with its implications for bandwidth and storage, we present schemes that combine region-of-interest isolation with JPEG and JPEG2000 compression at severe levels, and we test them using a publicly available government database of iris images. We show that it is possible to compress iris images to as little as 2 KB with minimal impact on recognition performance. Only some 2% to 3% of the bits in the IrisCode templates are changed by such severe image compression. Standard performance metrics such as error trade-off curves document very good recognition performance despite this reduction in data size by a net factor of 150, approaching a convergence of image data size and template size.

Full text

PDF (0.4 MB)

BibTeX record

  author =	 {Daugman, John and Downing, Cathryn},
  title = 	 {{Effect of severe image compression on iris recognition
  year = 	 2007,
  month = 	 may,
  url = 	 {},
  institution =  {University of Cambridge, Computer Laboratory},
  doi = 	 {10.48456/tr-685},
  number = 	 {UCAM-CL-TR-685}