用偏微分方程系统提升模糊文字图像的二值化效果
Partial differential equation system for binarization of degraded document images
- 构建弱耦合偏微分方程组，分别估计背景与前景
- 在86张退化文本图像上实现更优二值化效果
- 适合处理低质量文档图像的科研与工程场景
近年来，偏微分方程（PDE）系统已被成功应用于文本图像二值化，取得了良好效果。受DH模型启发，并结合一种新颖的图像建模方法，本文提出一种用于退化文本图像二值化的新型弱耦合PDE系统。该系统第一方程用于估计背景成分，包含扩散项和保真项；第二方程用于估计前景成分，包含扩散、保真及二值化源项。最终通过硬投影操作对估计的前景成分进行二值化处理。在86张退化文本图像上的实验结果表明，所提模型在处理退化文本图像方面具有显著优势。
原文摘要 · Abstract (English)
In recent years, partial differential equation (PDE) systems have been successfully applied to the binarization of text images, achieving promising results. Inspired by the DH model and incorporating a novel image modeling approach, this study proposes a new weakly coupled PDE system for degraded text image binarization. In this system, the first equation is designed to estimate the background component, incorporating both diffusion and fidelity terms. The second equation estimates the foreground component and includes diffusion, fidelity, and binarization source terms. The final binarization result is obtained by applying a hard projection to the estimated foreground component. Experimental results on 86 degraded text images demonstrate that the proposed model exhibits significant advantages in handling degraded text images.
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