Secure representation of images using multi-layer compression

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Abstract

We analyze the privacy preservation capabilities of a previously introduced multi-stage image representation framework where blocks of images with similar statistics are decomposed into different codebooks (dictionaries). There it was shown that at very low rate regimes, the method is capable of compressing images that come from the same family with results superior to those of the JPEG2000 codec. We consider two different elements to be added to the discussed approach to achieve a joint compression-encryption framework. The first visual scrambling is the random projections were the random matrix is kept secret between the encryption and decryption sides. We show that for the second approach, scrambling in the DCT domain, we can even slightly increase the compression performance of the multi-layer approach while making it safe against de-scrambling attacks. The experiments were carried out on the ExtendedYaleB database of facial images.

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Ferdowsi, S., Voloshynovskiy, S., Kostadinov, D., Korytkowski, M., & Scherer, R. (2015). Secure representation of images using multi-layer compression. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 9119, pp. 696–705). Springer Verlag. https://doi.org/10.1007/978-3-319-19324-3_62

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