Methods for accuracy-preserving acceleration of large-scale comparisons in CPU-based iris recognition systems

Methods for accuracy-preserving acceleration of large-scale comparisons in CPU-based iris recognition systems

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

Buy eFirst article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(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 to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
— Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

To confirm an individual's identity accurately and reliably iris recognition systems analyse the texture that is visible in the iris of the eye. The rich random pattern of the iris constitutes a powerful biometric characteristic suitable for biometric identification in large-scale deployments. Identification attempts or deduplication checks require an exhaustive one-to-many comparison. Hence, for large-scale biometric databases with millions of enrollees, the time required for a biometric identification is expected to significantly increase. In this study, the authors analyse techniques to accelerate Hamming distance-based comparisons of binary biometric reference data, i.e. iris-codes, in large-scale iris recognition systems, which preserve the biometric performance. The focus is put on software-based optimisations, an efficient two-step iris-code alignment process referred to as TripleA, and a combination thereof. Benchmarking the throughput and identifying potential bottlenecks of a portable commodity hardware-based iris recognition system is of particular interest. Based on the conducted experiments the authors point out practical boundaries of large-scale comparisons in central processing unit-based iris recognition systems, bridging the gap between the fields of iris recognition and software design.

Related content

This is a required field
Please enter a valid email address