YAN S H, ZONG C Q, GUO C L.A 3D facial feature template protection scheme based on line cloud[J].Journal of Henan Polytechnic University(Natural Science) ,2025,44(5):27-34.

DOI:10.16186/j.cnki.1673-9787.2024070041

Received: 2024/07/09

Revised: 2024/09/29

Published:2025/07/23

A 3D facial feature template protection scheme based on line cloud

Yan Shaohong1,2, Zong Chenqi1, Guo Chenliang1

1.College of  Science， North China University of Science and Technology， Tangshan  063210， Hebei， China；2.Hebei Provincial Key Laboratory of Data Science and Application， Tangshan  063210， Hebei， China

Abstract: Objectives Aiming at the problem that the storage security of 3D face point cloud template could not satisfy the privacy and security of recognition system， a face template protection scheme based on line cloud encryption was proposed ，and a 3D face recognition prototype system suitable for line cloud was designed according to the characteristics of the encrypted template. Methods In the registration stage， according to the serial number of face mark points （corner of the eye， nose tip， etc.）， the three-dimensional geometric information was obtained in the face space for storage， the template would not be leaked because of the sparse density of the marker matrix and less information. The rigid region subspace was built with the mark points as the center， and the traditional line cloud algorithm was improved to complete the line cloud encryption of the subspace point cloud template. In the matching stage， the face to be authenticated was subjected to rigid region segmentation to obtain a matrix of landmark points and establish a rigid region point cloud space. ICP（iterative closest point） algorithm was used to match the mark points of the face to be verified and the template face to get the transformation matrix. Using the transformation matrix to register the face to be verified with the encrypted template face， the distances between each rigid subregion point cloud and line cloud template were calculated. Different weights based on the accuracy of each regions were given to them， and the sum of the weighted distance would be used as the final judgment criterion to complete face recognition under encrypted conditions. Results The simulation results showed that this scheme could effectively resist privacy attacks and had good protection effects against brute-force attacks and line cloud attacks based on density； At the same time， it maintained a high recognition performance， with a true positive rate of 83.861%， a false positive case rate of 16.139%， and an equal error rate of 16.139% when achieving optimal recognition performance.  Conclusions The design of the algorithm and recognition model proposed in this article ensured its effectiveness as a biometric feature in the field of identity verification while protecting the geometric features of the 3D facial point cloud， which provided reference for the protection of 3D facial point cloud feature templates.

Key words:3D facial recognition;biometric template protection;marking points;rigid area;line cloud