TU Darmstadt / ULB / TUbiblio

Efficient, Accurate, and Rotation-Invariant Iris Code

Damer, Naser and Terhorst, Philipp and Braun, Andreas and Kuijper, Arjan (2017):
Efficient, Accurate, and Rotation-Invariant Iris Code.
In: IEEE Signal Processing Letters, 24 (8), pp. 1233-1237. ISSN 1070-9908,
DOI: 10.1109/LSP.2017.2719282,
[Article]

Abstract

The large scale of the recently demanded biometric systems has put a pressure on creating a more efficient, accurate, and private biometric solutions. Iris biometrics is one of the most distinctive and widely used biometric characteristics. High-performing iris representations suffer from the curse of rotation inconsistency. This is usually solved by assuming a range of rotational errors and performing a number of comparisons over this range, which results in a high computational effort and limits indexing and template protection. This work presents a generic and parameter-free transformation of binary iris representation into a rotation-invariant space. The goal is to perform accurate and efficient comparison and enable further indexing and template protection deployment. The proposed approach was tested on a database of 10 000 subjects of the ISYN1 iris database generated by CASIA. Besides providing a compact and rotational-invariant representation, the proposed approach reduced the equal error rate by more than 55% and the computational time by a factor of up to 44 compared to the original representation.

Item Type: Article
Erschienen: 2017
Creators: Damer, Naser and Terhorst, Philipp and Braun, Andreas and Kuijper, Arjan
Title: Efficient, Accurate, and Rotation-Invariant Iris Code
Language: English
Abstract:

The large scale of the recently demanded biometric systems has put a pressure on creating a more efficient, accurate, and private biometric solutions. Iris biometrics is one of the most distinctive and widely used biometric characteristics. High-performing iris representations suffer from the curse of rotation inconsistency. This is usually solved by assuming a range of rotational errors and performing a number of comparisons over this range, which results in a high computational effort and limits indexing and template protection. This work presents a generic and parameter-free transformation of binary iris representation into a rotation-invariant space. The goal is to perform accurate and efficient comparison and enable further indexing and template protection deployment. The proposed approach was tested on a database of 10 000 subjects of the ISYN1 iris database generated by CASIA. Besides providing a compact and rotational-invariant representation, the proposed approach reduced the equal error rate by more than 55% and the computational time by a factor of up to 44 compared to the original representation.

Journal or Publication Title: IEEE Signal Processing Letters
Journal volume: 24
Number: 8
Uncontrolled Keywords: Biometrics, Iris recognition, Feature selection, CRISP
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Mathematical and Applied Visual Computing
Date Deposited: 04 May 2020 10:06
DOI: 10.1109/LSP.2017.2719282
Official URL: https://doi.org/10.1109/LSP.2017.2719282
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details