Brown Michael S, Sun Mingxuan, Yang Ruigang, Yun Lin, Seales W Brent
School of Computer Engineering, Nanyang Technological University, Blk N4, 2A-32, Nanyang Avenue, Singapore 639798, Republic of Singapore.
IEEE Trans Pattern Anal Mach Intell. 2007 Nov;29(11):1904-16. doi: 10.1109/TPAMI.2007.1118.
This paper presents a framework to restore the 2D content printed on documents in the presence of geometric distortion and non-uniform illumination. Compared with textbased document imaging approaches that correct distortion to a level necessary to obtain sufficiently readable text or to facilitate optical character recognition (OCR), our work targets nontextual documents where the original printed content is desired. To achieve this goal, our framework acquires a 3D scan of the document's surface together with a high-resolution image. Conformal mapping is used to rectify geometric distortion by mapping the 3D surface back to a plane while minimizing angular distortion. This conformal "deskewing" assumes no parametric model of the document's surface and is suitable for arbitrary distortions. Illumination correction is performed by using the 3D shape to distinguish content gradient edges from illumination gradient edges in the high-resolution image. Integration is performed using only the content edges to obtain a reflectance image with significantly less illumination artifacts. This approach makes no assumptions about light sources and their positions. The results from the geometric and photometric correction are combined to produce the final output.
本文提出了一个框架，用于在存在几何失真和非均匀光照的情况下恢复文档上打印的二维内容。与基于文本的文档成像方法不同，后者将失真校正到获得足够可读文本或便于光学字符识别（OCR）所需的水平，我们的工作针对的是需要原始打印内容的非文本文档。为了实现这一目标，我们的框架获取文档表面的三维扫描以及高分辨率图像。共形映射用于通过将三维表面映射回平面同时最小化角度失真来校正几何失真。这种共形“去歪斜”不假设文档表面的参数模型，适用于任意失真。通过使用三维形状在高分辨率图像中区分内容梯度边缘和光照梯度边缘来进行光照校正。仅使用内容边缘进行积分以获得具有显著更少光照伪影的反射率图像。这种方法对光源及其位置不做任何假设。将几何校正和光度校正的结果相结合以产生最终输出。
