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A Visual Content Protection Evaluation Method for CS Coding Images

Published: 11 November 2020 Publication History

Abstract

Recently, the widespread application of image processing technology has caused special visual privacy issues while bringing convenience to our life. In particular, most of the current mainstream intelligent recognition algorithms rely on the detailed content of images, which has significantly increased the risk of personal privacy leakage. Therefore, we propose a multi-layer compressed sensing (CS) coding model, which ensures the security of image content and retains enough information for intelligent recognition at the same time. Besides, drawing on the idea of related feature mapping quality scores in image-quality assessment (IQA), we extract multi-frequency local binary pattern (LBP) and semantic salient features to estimate the content protection degree of CS images. Finally, experiments on three CS databases prove that the proposed method has better performance compared with other IQA methods.

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    WSSE '20: Proceedings of the 2nd World Symposium on Software Engineering
    September 2020
    329 pages
    ISBN:9781450387873
    DOI:10.1145/3425329
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    • Wuhan Univ.: Wuhan University, China
    • University of Electronic Science and Technology of China: University of Electronic Science and Technology of China

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    Published: 11 November 2020

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    Author Tags

    1. Content protection evaluation
    2. Multi-frequency LBP
    3. Multi-layer compressed sensing
    4. Semantic salient
    5. Visual privacy

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