Securing high resolution grayscale facial captures using a blockwise coevolutionary GA

作者：

Highlights：

• A specialized algorithm for high dimension optimization (49 k variables).

• Application specific in intelligent watermarking optimization of high resolution facial images.

• Significant fitness improvement (17% aggregated fitness improvement) and speedup is achieved.

• Sensitivity analysis for user-defined parameters of the algorithm based on GA.

摘要

•A specialized algorithm for high dimension optimization (49 k variables).•Application specific in intelligent watermarking optimization of high resolution facial images.•Significant fitness improvement (17% aggregated fitness improvement) and speedup is achieved.•Sensitivity analysis for user-defined parameters of the algorithm based on GA.

论文关键词：Biometrics,Intelligent watermarking,Evolutionary computation,Cooperative coevolution,Genetic algorithms,Grayscale texture masks

论文评审过程：Available online 2 July 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.06.043