Removing Shading Distortions in Camera-based Document Images Using Inpainting and Surface Fitting With Radial Basis Functions

Li Zhang, A. Yip, C. Tan
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引用次数: 17

Abstract

Shading distortions are often perceived in geometrically distorted document images due to the change of surface normal with respect to the illumination direction. Such distortions are undesirable because they hamper OCR performance tremendously even when the geometric distortions are corrected. In this paper, we propose an effective method that removes shading distortions in images of documents with various geometric shapes based on the notion of intrinsic images. We first try to derive the shading image using an inpainting technique with an automatic mask generation routine and then apply a surface fitting procedure with radial basis functions to remove pepper noises in the inpainted image and return a smooth shading image. Once the shading image is extracted, the reflectance image can be obtained automatically. Experiments on a wide range of distorted document images demonstrate a robust performance. Moreover, we also show its potential applications to the restoration of historical handwritten documents.
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在基于相机的文档图像中,使用径向基函数的补漆和表面拟合去除阴影失真
由于表面法线相对于照明方向的变化,在几何扭曲的文档图像中经常会感知到阴影失真。这样的失真是不可取的,因为它们极大地阻碍了OCR的性能,即使当几何失真被纠正。在本文中,我们提出了一种基于内在图像概念的有效方法来消除具有各种几何形状的文档图像中的阴影失真。我们首先尝试使用带有自动蒙版生成例程的着色技术来导出底纹图像,然后应用具有径向基函数的表面拟合过程来去除所绘制图像中的胡椒噪声并返回光滑的底纹图像。提取底纹图像后,自动获得反射率图像。在大范围的失真文档图像上的实验证明了该算法的鲁棒性。此外,我们还展示了它在历史手写文件修复中的潜在应用。
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