抗打印扫描和屏幕拍摄的字形扰动研究进展

本文介绍了字形扰动的应用场景，系统梳理了抗打印扫描和屏幕拍摄的字形扰动相关工作，将其分为两类：传统字形扰动方法和深度学习字形扰动方法。根据字符的属性特征，传统字形扰动方法细分为：像素翻转、高度调整、间距调整、笔画调整、特征点调整和骨架轮廓调整。深度学习字形扰动方法通过微调字符的高维特征以嵌入额外的信息，根据生成数据的性质，将其分为生成扰动文本图像和矢量字体两类。从鲁棒性、嵌入容量、复杂性等方面对比分析现有字形扰动方法的特点，最后对字形扰动研究面临的挑战和发展方向进行总结和展望。

Research Progress on Glyph Perturbation for Anti-print Scanning and Anti-screen Shooting

In this paper, we provide a review on the research progress of glyph perturbation. Following an introduction of the application scenarios of glyph perturbation, the existing works related to glyph perturbation for anti-print scanning and anti-screen shooting are systematically presented. The existing methods can be classified into two categories: traditional glyph perturbation and deep learning-based glyph perturbation. According to the attributes of characters, the former can be subdivided into pixel flipping, height adjustment, spacing adjustment, stroke adjustment, feature point adjustment, and skeleton adjustment. From the perspective of high-dimensional features, the latter slightly modifies the glyph of characters to embed additional messages. According to the property of the generated data, it can be divided into perturbed text image generation and vector font generation. The glyph perturbation methods are compared and analyzed in terms of robustness, embedding capacity, and complexity. Finally, the challenges and prospects of glyph perturbation are summarized.