A novel biometric image encryption algorithm based on compressed sensing and dual-tree complex wavelet transform

Ziru Zhao; Jiwen Dong; Hengian Li

doi:10.1117/12.2244927

29 August 2016 A novel biometric image encryption algorithm based on compressed sensing and dual-tree complex wavelet transform

Ziru Zhao, Jiwen Dong, Hengian Li

Author Affiliations +

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100332T (2016) https://doi.org/10.1117/12.2244927
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

This weakness is a critical threat for privacy with the widely used in the security applications. To protect the privacy and reduce the storage space during the biometric recognition, based on Compressed Sensing and Dual-tree Complex Wavelet Transform, we proposed a novel biometric image encryption algorithm. Firstly, the coefficients matrix are attained by performing DT-CWT on biometric image for its higher near shift-invariance property and greater directional selectivity. Then, the measurement matrix is generated by pseudo-random gauss measurement matrix which combined with one-dimensional (1-D) Logistic chaotic system. To improve the security of the encryption algorithm, the measurement matrix is scrambled and diffused by combining with 1-D Logistic mapping and Fibonacci scrambling algorithm. At last, the orthogonal matching pursuit (OMP) algorithm is employed to reconstruct the original image approximately. The experimental results demonstrate that the proposed encryption algorithm not only achieves the state of the art performance but also outperforms the existing image encryption methods with respect to the compressibility and the security.

Citation Download Citation

Ziru Zhao, Jiwen Dong, and Hengian Li "A novel biometric image encryption algorithm based on compressed sensing and dual-tree complex wavelet transform", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100332T (29 August 2016); https://doi.org/10.1117/12.2244927

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