English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Robust image watermarking that can resist camera shooting has become anactive research topic in recent years due to the increasing demand forpreventing sensitive information displayed on computer screens from beingcaptured. However, many mainstream schemes require human assistance during thewatermark detection process and cannot adapt to scenarios that requireprocessing a large number of images. Although deep learning-based schemesenable end-to-end watermark embedding and detection, their limitedgeneralization ability makes them vulnerable to failure in complex scenarios.In this paper, we propose a carefully crafted watermarking system that canresist camera shooting. The proposed scheme deals with two important problems:automatic watermark localization (AWL) and automatic watermark detection (AWD).AWL automatically identifies the region of interest (RoI), which containswatermark information, in the camera-shooting image by analyzing the localstatistical characteristics. Meanwhile, AWD extracts the hidden watermark fromthe identified RoI after applying perspective correction. Compared withprevious works, the proposed scheme is fully automatic, making it ideal forapplication scenarios. Furthermore, the proposed scheme is not limited to anyspecific watermark embedding strategy, allowing for improvements in thewatermark embedding and extraction procedure. Extensive experimental resultsand analysis show that the embedded watermark can be automatically and reliablyextracted from the camera-shooting image in different scenarios, demonstratingthe superiority and applicability of the proposed approach.

Automatic Localization and Detection Applicable to Robust Image Watermarking Resisting against Camera Shooting