CRCVNov 9, 2022

Composite Fixed-Length Ordered Features for Palmprint Template Protection with Diminished Performance Loss

arXiv:2211.04884v11 citationsh-index: 19
Originality Incremental advance
AI Analysis

This addresses privacy and security issues in palmprint recognition for biometric systems, offering an incremental improvement over existing methods.

The paper tackled the problem of palmprint template protection by proposing a composite fixed-length ordered feature operator, achieving low equal error rates of 0.17% and 0.19% on two databases with minimal precision loss.

Palmprint recognition has become more and more popular due to its advantages over other biometric modalities such as fingerprint, in that it is larger in area, richer in information and able to work at a distance. However, the issue of palmprint privacy and security (especially palmprint template protection) remains under-studied. Among the very few research works, most of them only use the directional and orientation features of the palmprint with transformation processing, yielding unsatisfactory protection and identification performance. Thus, this paper proposes a palmprint template protection-oriented operator that has a fixed length and is ordered in nature, by fusing point features and orientation features. Firstly, double orientations are extracted with more accuracy based on MFRAT. Then key points of SURF are extracted and converted to be fixed-length and ordered features. Finally, composite features that fuse up the double orientations and SURF points are transformed using the irreversible transformation of IOM to generate the revocable palmprint template. Experiments show that the EER after irreversible transformation on the PolyU and CASIA databases are 0.17% and 0.19% respectively, and the absolute precision loss is 0.08% and 0.07%, respectively, which proves the advantage of our method.

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