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arxiv 2001.07761 v1 pith:URYI5PP3 submitted 2020-01-21 cs.CV cs.LGeess.IV

Block-wise Scrambled Image Recognition Using Adaptation Network

classification cs.CV cs.LGeess.IV
keywords adaptationimageinformationnetworkperceptualblock-wisehidingimages
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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