Your browser does not support JavaScript!

Robust iris image segmentation

Robust iris image segmentation

For access to this article, please select a purchase option:

Buy chapter PDF
(plus tax if applicable)
Buy Knowledge Pack
10 chapters for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Iris and Periocular Biometric Recognition — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this chapter we presented current trends in iris segmentation, summarising the advances in state-of-the-art individual segmentation, shedding light on the pitfalls of NIR vs. VIS iris segmentation and illustrating means to tune existing iris segmentation towards specific datasets. We highlighted different forms of segmentation accuracy assessment and evaluated different approaches to combine segmentation algorithms. To get more stable results we integrated segmentation quality prediction in the fusion process.Tests on ground-truth confirm this positive effect across the board. For the goal of developing more robust iris segmentation techniques, multi-segmentation fusion and quality prediction can be a versatile tool to obtain more stable and more accurate results. However, performing fusion and running multiple segmentation algorithms impacts the processing time. This was not explicitly covered and further research on frame throughput might be necessary for video-based iris segmentation.

Chapter Contents:

  • 3.1 Introduction
  • 3.1.1 Segmentation accuracy
  • 3.1.2 Iris segmentation quality
  • 3.2 Advances in iris segmentation
  • 3.2.1 From circular models to active contours
  • 3.2.2 Near infrared vs. visible range segmentation
  • 3.2.3 Learning-based techniques
  • 3.2.4 Segmentation fusion
  • 3.3 Experiments
  • 3.3.1 Individual NIR vs. VIS performance
  • 3.3.2 Impact of tuning
  • 3.3.3 Combinations of segmentation performance
  • 3.4 Conclusion and future work
  • References

Inspec keywords: video signal processing; iris recognition; image segmentation

Other keywords: VIS iris segmentation; segmentation quality prediction; NIR iris segmentation; robust video iris image segmentation

Subjects: Video signal processing; Computer vision and image processing techniques; Image recognition

Preview this chapter:
Zoom in

Robust iris image segmentation, Page 1 of 2

| /docserver/preview/fulltext/books/sc/pbse005e/PBSE005E_ch3-1.gif /docserver/preview/fulltext/books/sc/pbse005e/PBSE005E_ch3-2.gif

Related content

This is a required field
Please enter a valid email address