Cancelable Iris template generation by aggregating patch level ordinal relations with its holistically extended performance and security analysis

作者：

Highlights：

• Iris Template protection.

• Distinctive iris feature extraction based on aggregation learning.

• Cancelable iris template generation based on ordinal filtering.

• Cancelable iris templates exhaustive security analysis.

摘要

•Iris Template protection.•Distinctive iris feature extraction based on aggregation learning.•Cancelable iris template generation based on ordinal filtering.•Cancelable iris templates exhaustive security analysis.

论文关键词：Ordinal measures,BioHashing,2N discretized BioPhasor,Cancelability,Security analysis (unlinkability,Revocability,Statistical,Non-invertibility),Domain knowledge,Aggregation learning

论文评审过程：Received 31 January 2020, Revised 22 July 2020, Accepted 31 August 2020, Available online 7 September 2020, Version of Record 23 September 2020.

论文官网地址：https://doi.org/10.1016/j.imavis.2020.104017