CTP-Net: Character Texture Perception Network for Document Image Forgery Localization

TL;DR

This paper introduces CTP-Net, a novel neural network that combines character texture and overall document texture features to effectively localize forgery regions in document images, even under post-processing conditions.

Contribution

The paper proposes a new Character Texture Perception Network (CTP-Net) that integrates OCR-based character features with texture analysis for improved forgery localization.

Findings

Outperforms existing forgery localization methods.

Effectively detects multi-scale forged regions.

Robust against post-processing operations.

Abstract

Due to the progression of information technology in recent years, document images have been widely disseminated on social networks. With the help of powerful image editing tools, document images are easily forged without leaving visible manipulation traces, which leads to severe issues if significant information is falsified for malicious use. Therefore, the research of document image forensics is worth further exploring. In this paper, we propose a Character Texture Perception Network (CTP-Net) to localize the forged regions in document images. Specifically, considering the characters with semantics in a document image are highly vulnerable, capturing the forgery traces is the key to localize the forged regions. We design a Character Texture Stream (CTS) based on optical character recognition to capture features of text areas that are essential components of a document image. Meanwhile, texture features of the whole document image are exploited by an Image Texture Stream (ITS). Combining the features extracted from the CTS and the ITS, the CTP-Net can reveal more subtle forgery traces from document images. Moreover, to overcome the challenge caused by the lack of fake document images, we design a data generation strategy that is utilized to construct a Fake Chinese Trademark dataset (FCTM). Experimental results on different datasets demonstrate that the proposed CTP-Net is able to localize multi-scale forged areas in document images, and outperform the state-of-the-art forgery localization methods, even though post-processing operations are applied.