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SDM: Semantic distortion measurement for video encryption

Hu, Yongquan, Zhou, Wei, Zhao, Shuxin, Chen, Zhibo and Li, Weiping 2018. SDM: Semantic distortion measurement for video encryption. Presented at: 13th IEEE International Conference on Automatic Face & Gesture Recognition, Xi'an, China, 15-19 May 2018. 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018). IEEE, pp. 764-768. 10.1109/FG.2018.00120

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Semantic information is important in video encryption. However, existing image quality assessment (IQA) methods, such as the peak signal to noise ratio (PSNR), are still widely applied to measure the encryption security. Generally, these traditional IQA methods aim to evaluate the image quality from the perspective of visual signal rather than semantic information. In this paper, we propose a novel semantic-level full-reference image quality assessment (FR-IQA) method named Semantic Distortion Measurement (SDM) to measure the degree of semantic distortion for video encryption. Then, based on a semantic saliency dataset, we verify that the proposed SDM method outperforms state-of-the-art algorithms. Furthermore, we construct a Region Of Semantic Saliency (ROSS) video encryption system to demonstrate the effectiveness of our proposed SDM method in the practical application.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Publisher: IEEE
Last Modified: 24 Aug 2023 14:30

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