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

• URL: http://arxiv.org/abs/2211.04884v1
• Date: Wed, 9 Nov 2022 13:40:04 GMT
• Title: Composite Fixed-Length Ordered Features for Palmprint Template Protection with Diminished Performance Loss
• Authors: Weiqiang Zhao, Heng Zhao, Zhicheng Cao, and Liaojun Pang
• Abstract summary: 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. Experiments show that the EER after irreversible transformation on the PolyU and CASIA databases are 0.17% and 0.19% respectively.
• Score: 3.8586071087712033
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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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