  In this study, a perceptually hidden object-recognition method is
investigated to generate secure images recognizable by humans but not machines.
Hence, both the perceptual information hiding and the corresponding object
recognition methods should be developed. Block-wise image scrambling is
introduced to hide perceptual information from a third party. In addition, an
adaptation network is proposed to recognize those scrambled images.
Experimental comparisons conducted using CIFAR datasets demonstrated that the
proposed adaptation network performed well in incorporating simple perceptual
information hiding into DNN-based image classification.
