Fast Frequency Domain Screen-Shooting Watermarking Algorithm Based on ORB Feature Points

Yu Bai, Li Li, Shanqing Zhang (), Jianfeng Lu and Mahmoud Emam ()
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Yu Bai: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Li Li: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Shanqing Zhang: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Jianfeng Lu: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Mahmoud Emam: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China

Mathematics, 2023, vol. 11, issue 7, 1-22

Abstract: With high performances of image capturing tools, image information can be easily obtained by screenshots that make image copyright protection a challenging task. The existing screen-shooting watermarking algorithms suffer from a huge running time, in addition to their low robustness against different screenshot attacks, such as different distances and capturing angles of the screenshots. In this paper, a fast and robust high-capacity flexible watermarking algorithm for screenshot images is proposed. Firstly, Oriented FAST and Rotated BRIEF (ORB) feature points are extracted from the input image. Secondly, the feature points are then sorted in a descending order according to their response values. Then, the first five non-overlapping feature points are selected for the embedding by using Hamming window-based filtering method. Furthermore, we exploit the multi-resolution property of Discrete Wavelet Transform (DWT) and energy compaction property of Singular Value Decomposition (SVD) to embed the watermark. Therefore, the classical DWT combined with Singular Value Decomposition (SVD) are adopted to improve the robustness and capacity of the proposed watermarking algorithm. At the extraction side, the sum of the response values for the three RGB channels of the color-ripped image is calculated to improve the feature point localization accuracy. Experimental results show that the proposed screen-shooting watermarking algorithm improves running speed while ensuring the robustness. Furthermore, it has less time complexity and high robustness compared with the state-of-the-art watermarking algorithms against different screenshot attacks.

Keywords: screen capture; screen-shooting watermarking; ORB feature points; DWT; SVD; hamming window; robust watermarking (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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