Improved Magic Square Transform Combined with Double Random Phase Encoding for Iris Recognition

To address the issue of iris template leakage using irreversible transformation, this study proposes a new double iris template protection method that combines an improved magic square transformation with Double Random Phase Encoding (DRPE). Firstly, the user's iris features using the log-Gabor transform were extracted, then scrambling iterations and transformation matrix parameters. The iris feature matrix is divided into non-overlapping blocks and scrambled for the first layer of encryption protection using the improved magic square method. Next, in the fractional Fourier transform domain, DRPE is applied to construct an encrypted feature vector. This involves using a user-defined mask M1 and a second mask M2 derived from the user’s other iris image, for a second layer of encryption on the scrambled matrix. Finally, encrypted templates are matched for recognition using Hamming distance. Images from the CASIA-IrisV3-Interval, MMU-V1, and CASIA-IrisV4-Lamp iris databases were used to test the algorithm's performance. Results demonstrate that the proposed method achieves an accuracy of 98.93%, can generate a total of 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> possible templates, and requires 314<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">52×624</sup> ×10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> attempts to recover the original data. This approach meets the standards for irreversibility, revocability, and unlinkability in biometric template protection.

Authors

Institutions

Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1109/cacml64929.2025.11010947
Citations
1
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
1.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improved Magic Square Transform Combined with Double Random Phase Encoding for Iris Recognition

Xue Zou, Yanna Gao
1 citations
Biometric Identification and Security
1.49
article

Improved Magic Square Transform Combined with Double Random Phase Encoding for Iris Recognition

Xue Zou, Yanna Gao
article en
1 citations

Abstract

To address the issue of iris template leakage using irreversible transformation, this study proposes a new double iris template protection method that combines an improved magic square transformation with Double Random Phase Encoding (DRPE). Firstly, the user's iris features using the log-Gabor transform were extracted, then scrambling iterations and transformation matrix parameters. The iris feature matrix is divided into non-overlapping blocks and scrambled for the first layer of encryption protection using the improved magic square method. Next, in the fractional Fourier transform domain, DRPE is applied to construct an encrypted feature vector. This involves using a user-defined mask M1 and a second mask M2 derived from the user’s other iris image, for a second layer of encryption on the scrambled matrix. Finally, encrypted templates are matched for recognition using Hamming distance. Images from the CASIA-IrisV3-Interval, MMU-V1, and CASIA-IrisV4-Lamp iris databases were used to test the algorithm's performance. Results demonstrate that the proposed method achieves an accuracy of 98.93%, can generate a total of 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> possible templates, and requires 314<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">52×624</sup> ×10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> attempts to recover the original data. This approach meets the standards for irreversibility, revocability, and unlinkability in biometric template protection.

East University Of Heilongjiang (CN)
Research and Development
Openalex Percentile: Top 19%
Biometric Identification and Security
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Improved Magic Square Transform Combined with Double Random Phase Encoding for Iris Recognition — Xue Zou, Yanna Gao · (2025) | TGRS Research Map | TGRS