Binarization of Badly Illuminated Document Images through Shading Estimation and Compensation
Shijian Lu, C.L. Tan · Proceedings of the International Conference on Document Analysis and Recognition · 2007
This paper presents a document image binarization technique that segments text from badly illuminated document images. Based on the observations that text documents normally lie over a planar or smoothly curved surface and have a uniformly colored background, badly illuminated document images are binarized by using a smoothing polynomial surface, which estimates the shading variation and compensates the shading degradation based on the estimated shading variation. Badly illuminated document images are accordingly binarized through the global thresholding of the compensated document images. Compared with the reported methods, the proposed technique is tolerant to the variations in text size and document contrast. At the same time, it is much faster and able to produce a binary text image with little background noise.