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

TL;DR

This paper introduces an automatic, fully-automatic watermarking system that can reliably detect and localize watermarks in images captured by cameras, overcoming limitations of previous methods and enhancing robustness against camera shooting.

Contribution

The paper presents a novel automatic watermark localization and detection scheme that does not require human assistance and is adaptable to various embedding strategies.

Findings

Successfully localizes watermark regions automatically in camera-shooting images.

Reliable extraction of watermarks across diverse scenarios demonstrated.

System is compatible with different watermark embedding methods.

Abstract

Robust image watermarking that can resist camera shooting has become an active research topic in recent years due to the increasing demand for preventing sensitive information displayed on computer screens from being captured. However, many mainstream schemes require human assistance during the watermark detection process and cannot adapt to scenarios that require processing a large number of images. Although deep learning-based schemes enable end-to-end watermark embedding and detection, their limited generalization ability makes them vulnerable to failure in complex scenarios. In this paper, we propose a carefully crafted watermarking system that can resist 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 contains watermark information, in the camera-shooting image by analyzing the local statistical characteristics. Meanwhile, AWD extracts the hidden watermark from the identified RoI after applying perspective correction. Compared with previous works, the proposed scheme is fully automatic, making it ideal for application scenarios. Furthermore, the proposed scheme is not limited to any specific watermark embedding strategy, allowing for improvements in the watermark embedding and extraction procedure. Extensive experimental results and analysis show that the embedded watermark can be automatically and reliably extracted from the camera-shooting image in different scenarios, demonstrating the superiority and applicability of the proposed approach.