IrisCode decompression based on the dependence between its bit pairs
IrisCode is an iris recognition algorithm developed in 1993 and continuously improved by Daugman. Understanding IrisCode's properties is extremely important because over 60 million people have been mathematically enrolled by the algorithm. In this paper, IrisCode is proved to be a compression a...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/99407 http://hdl.handle.net/10220/13493 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-99407 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-994072020-05-28T07:18:02Z IrisCode decompression based on the dependence between its bit pairs Kong, Adams Wai-Kin. School of Computer Engineering Forensics and Security Lab DRNTU::Engineering::Computer science and engineering IrisCode is an iris recognition algorithm developed in 1993 and continuously improved by Daugman. Understanding IrisCode's properties is extremely important because over 60 million people have been mathematically enrolled by the algorithm. In this paper, IrisCode is proved to be a compression algorithm, which is to say its templates are compressed iris images. In our experiments, the compression ratio of these images is 1:655. An algorithm is designed to perform this decompression by exploiting a graph composed of the bit pairs in IrisCode, prior knowledge from iris image databases, and the theoretical results. To remove artifacts, two postprocessing techniques that carry out optimization in the Fourier domain are developed. Decompressed iris images obtained from two public iris image databases are evaluated by visual comparison, two objective image quality assessment metrics, and eight iris recognition methods. The experimental results show that the decompressed iris images retain iris texture that their quality is roughly equivalent to a JPEG quality factor of 10 and that the iris recognition methods can match the original images with the decompressed images. This paper also discusses the impacts of these theoretical and experimental findings on privacy and security. 2013-09-16T07:50:51Z 2019-12-06T20:06:53Z 2013-09-16T07:50:51Z 2019-12-06T20:06:53Z 2012 2012 Journal Article Kong, A. W.-K. (2012). IrisCode Decompression Based on the Dependence between Its Bit Pairs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(3), 506-520. 0162-8828 https://hdl.handle.net/10356/99407 http://hdl.handle.net/10220/13493 10.1109/TPAMI.2011.159 en IEEE transactions on pattern analysis and machine intelligence © 2012 IEEE |
institution |
Nanyang Technological University |
building |
NTU Library |
country |
Singapore |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Computer science and engineering |
spellingShingle |
DRNTU::Engineering::Computer science and engineering Kong, Adams Wai-Kin. IrisCode decompression based on the dependence between its bit pairs |
description |
IrisCode is an iris recognition algorithm developed in 1993 and continuously improved by Daugman. Understanding IrisCode's properties is extremely important because over 60 million people have been mathematically enrolled by the algorithm. In this paper, IrisCode is proved to be a compression algorithm, which is to say its templates are compressed iris images. In our experiments, the compression ratio of these images is 1:655. An algorithm is designed to perform this decompression by exploiting a graph composed of the bit pairs in IrisCode, prior knowledge from iris image databases, and the theoretical results. To remove artifacts, two postprocessing techniques that carry out optimization in the Fourier domain are developed. Decompressed iris images obtained from two public iris image databases are evaluated by visual comparison, two objective image quality assessment metrics, and eight iris recognition methods. The experimental results show that the decompressed iris images retain iris texture that their quality is roughly equivalent to a JPEG quality factor of 10 and that the iris recognition methods can match the original images with the decompressed images. This paper also discusses the impacts of these theoretical and experimental findings on privacy and security. |
author2 |
School of Computer Engineering |
author_facet |
School of Computer Engineering Kong, Adams Wai-Kin. |
format |
Article |
author |
Kong, Adams Wai-Kin. |
author_sort |
Kong, Adams Wai-Kin. |
title |
IrisCode decompression based on the dependence between its bit pairs |
title_short |
IrisCode decompression based on the dependence between its bit pairs |
title_full |
IrisCode decompression based on the dependence between its bit pairs |
title_fullStr |
IrisCode decompression based on the dependence between its bit pairs |
title_full_unstemmed |
IrisCode decompression based on the dependence between its bit pairs |
title_sort |
iriscode decompression based on the dependence between its bit pairs |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/99407 http://hdl.handle.net/10220/13493 |
_version_ |
1681058380280496128 |