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Cancelable face recognition using phase retrieval and complex principal component analysis network

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Abstract

Considering the necessity of sensitive information protection in face image, a cancelable template generation model for multimodal face images is proposed in this paper. Firstly, the visual meaningful face images are transformed into phase-only functions through phase retrieval in gyrator domain. Then random projection and chaotic-based mask are constituted into modulation for achieving revocability and distinguishability. The interim results are mapped to a higher-dimensional space using random Fourier features. Followed by two-stage complex-valued principal component analysis, the convolutional filters are learned efficiently. Together with binary hashing and decimal coding, local histogram features are obtained and forwarded to SVM for training and recognition. Experiments performed on three publicly multimodal datasets demonstrate that the proposed algorithm can obtain higher accuracy, precision, recall and F-score in comparison with some existing algorithms while the templates are non-invertible and easy to revoke.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61601311), Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (MIMS23-08), Science and Technology Innovation Talent Project of Education Department of Henan Province (No. 23HASTIT030), Science and Technology Planning Project of Jiaxing (2022AY10021) and Scientific Research Project of Education Department of Jilin Province (JJKH20240586KJ). The authors greatly appreciate the anonymous reviewers for their helpful suggestions.

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Authors and Affiliations

  1. College of Information Engineering, Capital Normal University, Beijing, 100048, China

    Zhuhong Shao, Leding Li, Zuowei Zhang & Yuanyuan Shang

  2. Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004, China

    Zhuhong Shao

  3. School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China

    Bicao Li

  4. College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China

    Xilin Liu

  5. College of Information Science and Engineering, Jiaxing University, Jiaxing, 314001, China

    Bin Chen

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  1. Zhuhong Shao
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  2. Leding Li
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  3. Zuowei Zhang
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  4. Bicao Li
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  5. Xilin Liu
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  6. Yuanyuan Shang
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  7. Bin Chen
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Contributions

Z.S. and L.L.: Methodology, software, writing—original draft. Z.Z., B.L., and X.L.: Software; Visualization. Y.S. and B.C.: Writing—review & editing.

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Correspondence to Zhuhong Shao.

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Shao, Z., Li, L., Zhang, Z. et al. Cancelable face recognition using phase retrieval and complex principal component analysis network. Machine Vision and Applications 35, 12 (2024). https://doi.org/10.1007/s00138-023-01496-x

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